R/lmreg-internal.R

In marutter/lmreg: Data and Functions Used in Linear Models and Regression with R: An Integrated Approach

..airspeed <-
structure(list(V1 = structure(c(18L, 2L, 1L, 3L, 4L, 7L, 5L, 
8L, 6L, 10L, 11L, 12L, 14L, 9L, 13L, 13L, 15L, 16L, 17L), .Label = c("-0.023", 
"-0.024", "0.001", "0.008", "0.023", "0.028", "0.029", "0.033", 
"0.037", "0.045", "0.057", "0.074", "0.079", "0.08", "0.095", 
"0.101", "0.111", "Posmaxspeed"), class = "factor"), V2 = structure(c(7L, 
1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 
5L, 6L), .Label = c("4.8", "4.9", "5", "5.1", "5.2", "5.3", "Reynolds"
), class = "factor"), V3 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("0.01", 
"0.015", "0.02", "Ribht"), class = "factor")), class = "data.frame", row.names = c(NA, 
-19L))
..appletree <-
structure(list(V1 = structure(c(7L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 
3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 
1L), .Label = c("0", "1", "2", "3", "4", "5", "Treatment"), class = "factor"), 
    V2 = structure(c(5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L
    ), .Label = c("1", "2", "3", "4", "Block"), class = "factor"), 
    V3 = structure(c(22L, 14L, 14L, 9L, 6L, 8L, 11L, 19L, 7L, 
    10L, 5L, 10L, 1L, 12L, 18L, 20L, 2L, 16L, 17L, 15L, 1L, 21L, 
    3L, 13L, 4L), .Label = c("10.1", "10.2", "10.3", "10.5", 
    "5.5", "5.7", "6", "6.1", "6.8", "7", "7.6", "7.7", "8.1", 
    "8.2", "8.5", "8.7", "9", "9.1", "9.4", "9.7", "9.9", "Volume"
    ), class = "factor"), V4 = structure(c(24L, 14L, 10L, 6L, 
    1L, 4L, 5L, 15L, 3L, 4L, 2L, 11L, 16L, 9L, 8L, 13L, 18L, 
    12L, 7L, 17L, 20L, 22L, 23L, 19L, 21L), .Label = c("189", 
    "205", "209", "210", "222", "234", "238", "243", "254", "271", 
    "276", "279", "286", "287", "290", "301", "307", "312", "344", 
    "348", "357", "371", "375", "Weight"), class = "factor")), class = "data.frame", row.names = c(NA, 
-25L))
..Birthwt <-
structure(list(V1 = structure(c(3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L), .Label = c("0", "1", "LOW"), class = "factor"), 
    V2 = structure(c(25L, 6L, 20L, 7L, 8L, 5L, 8L, 9L, 4L, 16L, 
    13L, 6L, 6L, 9L, 17L, 5L, 5L, 2L, 12L, 7L, 15L, 19L, 18L, 
    23L, 15L, 12L, 15L, 4L, 16L, 13L, 4L, 4L, 11L, 22L, 12L, 
    12L, 16L, 6L, 14L, 18L, 20L, 8L, 6L, 10L, 8L, 5L, 5L, 19L, 
    6L, 11L, 9L, 9L, 10L, 9L, 17L, 6L, 3L, 8L, 17L, 7L, 4L, 4L, 
    10L, 11L, 15L, 13L, 7L, 11L, 15L, 7L, 9L, 9L, 18L, 10L, 3L, 
    3L, 5L, 12L, 19L, 7L, 10L, 9L, 19L, 17L, 7L, 10L, 4L, 6L, 
    10L, 23L, 9L, 11L, 8L, 6L, 12L, 3L, 16L, 16L, 6L, 6L, 17L, 
    11L, 6L, 11L, 10L, 7L, 12L, 17L, 9L, 5L, 3L, 19L, 5L, 16L, 
    20L, 7L, 15L, 1L, 15L, 12L, 3L, 7L, 13L, 8L, 9L, 12L, 18L, 
    22L, 6L, 11L, 24L, 15L, 16L, 21L, 12L, 12L, 14L, 10L, 11L, 
    11L, 8L, 19L, 6L, 12L, 3L, 12L, 7L, 8L, 11L, 8L, 7L, 12L, 
    6L, 6L, 13L, 11L, 4L, 7L, 9L, 14L, 7L, 4L, 12L, 7L, 5L, 5L, 
    7L, 8L, 13L, 18L, 2L, 10L, 7L, 11L, 2L, 10L, 17L, 9L, 4L, 
    10L, 4L, 13L, 7L, 13L, 1L, 15L, 1L, 10L, 4L, 8L), .Label = c("14", 
    "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
    "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", 
    "35", "36", "45", "AGE"), class = "factor"), V3 = structure(c(76L, 
    51L, 42L, 5L, 7L, 6L, 21L, 15L, 4L, 20L, 11L, 72L, 39L, 72L, 
    6L, 1L, 1L, 75L, 15L, 17L, 17L, 18L, 1L, 59L, 17L, 17L, 46L, 
    19L, 39L, 47L, 11L, 11L, 68L, 18L, 42L, 22L, 34L, 33L, 21L, 
    60L, 8L, 53L, 56L, 26L, 44L, 68L, 68L, 28L, 28L, 12L, 66L, 
    17L, 24L, 26L, 72L, 12L, 9L, 9L, 40L, 4L, 16L, 16L, 16L, 
    9L, 34L, 29L, 48L, 12L, 64L, 35L, 43L, 10L, 39L, 12L, 10L, 
    31L, 61L, 34L, 30L, 18L, 57L, 27L, 49L, 9L, 23L, 20L, 17L, 
    5L, 26L, 50L, 22L, 29L, 30L, 62L, 72L, 31L, 31L, 41L, 37L, 
    37L, 32L, 9L, 52L, 9L, 9L, 17L, 63L, 10L, 48L, 17L, 49L, 
    54L, 17L, 26L, 14L, 49L, 30L, 31L, 26L, 17L, 72L, 43L, 44L, 
    12L, 25L, 26L, 17L, 49L, 17L, 13L, 20L, 17L, 26L, 55L, 5L, 
    66L, 39L, 74L, 24L, 28L, 45L, 5L, 69L, 12L, 26L, 70L, 39L, 
    58L, 42L, 4L, 22L, 67L, 3L, 10L, 14L, 33L, 26L, 17L, 26L, 
    26L, 65L, 9L, 5L, 8L, 38L, 9L, 18L, 1L, 73L, 3L, 9L, 55L, 
    19L, 5L, 12L, 17L, 36L, 26L, 17L, 9L, 17L, 41L, 5L, 57L, 
    2L, 72L, 1L, 71L, 36L, 26L), .Label = c("100", "101", "102", 
    "103", "105", "107", "108", "109", "110", "112", "113", "115", 
    "116", "117", "118", "119", "120", "121", "122", "123", "124", 
    "125", "127", "128", "129", "130", "131", "132", "133", "134", 
    "135", "137", "138", "140", "141", "142", "147", "148", "150", 
    "153", "154", "155", "158", "160", "165", "167", "168", "169", 
    "170", "175", "182", "184", "185", "186", "187", "189", "190", 
    "200", "202", "215", "229", "235", "241", "250", "80", "85", 
    "89", "90", "91", "92", "94", "95", "96", "97", "98", "LWT"
    ), class = "factor"), V4 = structure(c(4L, 3L, 1L, 2L, 2L, 
    2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 2L, 1L, 
    2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 
    3L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
    1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 2L, 2L, 3L, 
    2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 3L, 2L, 2L, 2L, 
    3L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 3L, 1L, 
    2L, 2L, 2L, 1L, 1L, 2L, 2L, 3L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 1L, 3L, 2L, 3L, 1L, 2L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L, 
    2L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 3L, 2L), .Label = c("1", "2", "3", "RACE"), class = "factor"), 
    V5 = structure(c(3L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
    2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 
    1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
    1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 
    1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 
    2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 
    2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 
    1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L
    ), .Label = c("0", "1", "SMOKE"), class = "factor"), V6 = structure(c(5L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
    3L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 
    2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1", 
    "2", "3", "PTL"), class = "factor"), V7 = structure(c(3L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 
    1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L), .Label = c("0", "1", 
    "HT"), class = "factor"), V8 = structure(c(3L, 2L, 1L, 1L, 
    2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 
    2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 
    1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1", "UI"), class = "factor"), 
    V9 = structure(c(7L, 1L, 4L, 2L, 3L, 1L, 1L, 2L, 2L, 2L, 
    1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 4L, 1L, 2L, 3L, 4L, 2L, 1L, 
    3L, 1L, 1L, 3L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 3L, 3L, 1L, 3L, 
    2L, 3L, 3L, 2L, 1L, 1L, 1L, 5L, 1L, 3L, 1L, 2L, 1L, 1L, 3L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 2L, 3L, 6L, 2L, 
    3L, 1L, 3L, 2L, 1L, 1L, 1L, 2L, 5L, 1L, 1L, 2L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 
    2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 3L, 5L, 3L, 2L, 3L, 2L, 
    1L, 2L, 1L, 1L, 3L, 2L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 1L, 2L, 
    2L, 1L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 
    1L, 3L, 3L, 1L, 1L, 1L, 2L, 3L, 1L, 1L, 1L, 1L, 4L, 2L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 5L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 
    1L, 1L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 1L, 3L, 3L, 1L, 1L, 4L
    ), .Label = c("0", "1", "2", "3", "4", "6", "FTV"), class = "factor"), 
    V10 = structure(c(134L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 
    48L, 49L, 50L, 51L, 52L, 53L, 53L, 54L, 54L, 55L, 56L, 57L, 
    58L, 59L, 59L, 60L, 61L, 62L, 62L, 63L, 64L, 64L, 64L, 64L, 
    65L, 65L, 66L, 66L, 66L, 66L, 67L, 68L, 69L, 70L, 71L, 71L, 
    71L, 72L, 72L, 73L, 74L, 74L, 74L, 75L, 76L, 77L, 78L, 79L, 
    79L, 80L, 80L, 80L, 81L, 81L, 82L, 82L, 83L, 84L, 85L, 85L, 
    86L, 87L, 87L, 87L, 88L, 89L, 90L, 90L, 91L, 92L, 93L, 94L, 
    95L, 96L, 97L, 98L, 99L, 100L, 101L, 101L, 102L, 103L, 104L, 
    104L, 105L, 105L, 106L, 107L, 108L, 108L, 108L, 108L, 109L, 
    110L, 111L, 112L, 112L, 112L, 113L, 114L, 115L, 116L, 117L, 
    117L, 118L, 118L, 119L, 120L, 121L, 121L, 122L, 123L, 124L, 
    124L, 125L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 
    133L, 1L, 2L, 3L, 4L, 5L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
    13L, 13L, 13L, 14L, 15L, 16L, 16L, 17L, 18L, 18L, 19L, 20L, 
    21L, 22L, 22L, 23L, 24L, 25L, 25L, 26L, 27L, 27L, 28L, 29L, 
    30L, 30L, 31L, 32L, 32L, 32L, 33L, 34L, 34L, 35L, 36L, 37L, 
    38L, 39L, 40L, 40L, 40L, 41L, 41L, 41L, 41L), .Label = c("1021", 
    "1135", "1330", "1474", "1588", "1701", "1729", "1790", "1818", 
    "1885", "1893", "1899", "1928", "1936", "1970", "2055", "2082", 
    "2084", "2100", "2125", "2126", "2187", "2211", "2225", "2240", 
    "2282", "2296", "2301", "2325", "2353", "2367", "2381", "2395", 
    "2410", "2414", "2424", "2438", "2442", "2450", "2466", "2495", 
    "2523", "2551", "2557", "2594", "2600", "2622", "2637", "2663", 
    "2665", "2722", "2733", "2750", "2769", "2778", "2782", "2807", 
    "2821", "2835", "2836", "2863", "2877", "2906", "2920", "2948", 
    "2977", "2992", "3005", "3033", "3042", "3062", "3076", "3080", 
    "3090", "3100", "3104", "3132", "3147", "3175", "3203", "3225", 
    "3232", "3234", "3260", "3274", "3303", "3317", "3321", "3331", 
    "3374", "3402", "3416", "3430", "3444", "3459", "3460", "3473", 
    "3475", "3487", "3544", "3572", "3586", "3600", "3614", "3629", 
    "3637", "3643", "3651", "3699", "3728", "3756", "3770", "3790", 
    "3799", "3827", "3856", "3860", "3884", "3912", "3940", "3941", 
    "3969", "3983", "3997", "4054", "4111", "4153", "4167", "4174", 
    "4238", "4593", "4990", "709", "BWT"), class = "factor")), class = "data.frame", row.names = c(NA, 
-190L))
..denim_abr <-
structure(list(V1 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L), .Label = c("1", "2", "3", "Laundry"), class = "factor"), 
    V2 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L), .Label = c("1", "2", "3", "Denim"
    ), class = "factor"), V3 = structure(c(91L, 83L, 85L, 79L, 
    56L, 90L, 87L, 63L, 88L, 89L, 78L, 81L, 75L, 65L, 53L, 84L, 
    80L, 61L, 68L, 69L, 58L, 72L, 73L, 46L, 77L, 45L, 36L, 10L, 
    1L, 48L, 59L, 39L, 47L, 32L, 14L, 33L, 34L, 52L, 41L, 6L, 
    13L, 3L, 27L, 26L, 29L, 2L, 20L, 31L, 28L, 24L, 19L, 12L, 
    40L, 17L, 23L, 5L, 22L, 43L, 21L, 7L, 11L, 60L, 71L, 64L, 
    74L, 38L, 50L, 66L, 55L, 62L, 76L, 15L, 35L, 49L, 44L, 18L, 
    51L, 30L, 86L, 4L, 67L, 8L, 16L, 42L, 25L, 57L, 9L, 54L, 
    82L, 37L, 70L), .Label = c("1.2398", "1.297", "1.3373", "1.3626", 
    "1.3799", "1.4007", "1.5106", "1.5333", "1.6144", "1.6737", 
    "1.7043", "1.717", "1.7422", "1.7627", "1.8032", "1.8093", 
    "1.8357", "1.8494", "1.8638", "1.88", "1.8818", "1.8926", 
    "1.8986", "1.8988", "1.9291", "1.9434", "2.0123", "2.0151", 
    "2.019", "2.0292", "2.0632", "2.0989", "2.1132", "2.1229", 
    "2.1526", "2.1572", "2.1734", "2.2233", "2.2389", "2.2421", 
    "2.2467", "2.26", "2.2674", "2.2728", "2.3173", "2.3802", 
    "2.4392", "2.4494", "2.4623", "2.4641", "2.4745", "2.5048", 
    "2.5685", "2.5819", "2.6048", "2.6289", "2.6441", "2.6499", 
    "2.6677", "2.679", "2.7016", "2.7132", "2.7742", "2.775", 
    "2.7948", "2.8179", "2.8369", "2.842", "2.8887", "2.9636", 
    "2.9687", "3.0114", "3.0123", "3.0185", "3.03", "3.0655", 
    "3.0909", "3.1223", "3.1334", "3.1351", "3.1506", "3.1609", 
    "3.2218", "3.2388", "3.3547", "3.4265", "3.4383", "3.4454", 
    "3.6696", "3.8816", "Abrasion"), class = "factor")), class = "data.frame", row.names = c(NA, 
-91L))
..Drugprice <-
structure(list(V1 = structure(c(14L, 5L, 3L, 6L, 9L, 7L, 2L, 
8L, 1L, 4L, 12L, 13L, 11L, 10L), .Label = c("1.35", "14.54", 
"2.7", "23.74", "3.32", "32.09", "33.98", "49.48", "5.04", "58.86", 
"7.16", "7.97", "9.92", "OriginatorMPR"), class = "factor"), 
    V2 = structure(c(14L, 4L, 2L, 13L, 3L, 11L, 8L, 5L, 1L, 7L, 
    6L, 10L, 9L, 12L), .Label = c("0.11", "1.2", "1.28", "1.43", 
    "11.22", "2.63", "2.71", "3.07", "3.93", "3.95", "5.28", 
    "5.32", "6.06", "GenericMPR"), class = "factor")), class = "data.frame", row.names = c(NA, 
-14L))
..Girlgrowth <-
structure(list(V1 = structure(c(7L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L), .Label = c("10", "11", "12", "7", "8", "9", "Age"), class = "factor"), 
    V2 = structure(c(388L, 29L, 62L, 45L, 76L, 98L, 88L, 52L, 
    23L, 75L, 8L, 73L, 74L, 110L, 89L, 59L, 151L, 25L, 32L, 2L, 
    6L, 74L, 44L, 44L, 68L, 24L, 4L, 40L, 53L, 141L, 70L, 48L, 
    49L, 46L, 54L, 51L, 25L, 37L, 87L, 103L, 35L, 26L, 15L, 95L, 
    28L, 38L, 3L, 70L, 1L, 18L, 68L, 73L, 129L, 139L, 86L, 113L, 
    16L, 81L, 70L, 34L, 7L, 100L, 2L, 5L, 66L, 102L, 108L, 23L, 
    40L, 27L, 1L, 34L, 87L, 80L, 125L, 30L, 33L, 68L, 8L, 51L, 
    56L, 7L, 30L, 156L, 34L, 26L, 43L, 74L, 36L, 61L, 48L, 30L, 
    90L, 39L, 6L, 34L, 130L, 143L, 55L, 19L, 6L, 19L, 113L, 142L, 
    30L, 64L, 13L, 61L, 50L, 57L, 60L, 117L, 18L, 119L, 74L, 
    43L, 25L, 20L, 34L, 63L, 51L, 10L, 54L, 26L, 35L, 31L, 91L, 
    33L, 44L, 15L, 107L, 167L, 99L, 103L, 132L, 12L, 21L, 53L, 
    41L, 46L, 27L, 9L, 62L, 100L, 64L, 42L, 104L, 70L, 98L, 106L, 
    134L, 42L, 168L, 77L, 74L, 73L, 147L, 210L, 215L, 101L, 11L, 
    74L, 129L, 124L, 192L, 134L, 64L, 102L, 72L, 164L, 74L, 161L, 
    118L, 136L, 135L, 94L, 209L, 84L, 174L, 74L, 177L, 159L, 
    204L, 118L, 90L, 182L, 58L, 224L, 148L, 99L, 98L, 67L, 162L, 
    216L, 69L, 70L, 142L, 150L, 142L, 179L, 216L, 83L, 104L, 
    144L, 94L, 34L, 91L, 94L, 60L, 73L, 160L, 31L, 110L, 79L, 
    198L, 82L, 117L, 71L, 218L, 91L, 44L, 120L, 93L, 96L, 163L, 
    121L, 137L, 22L, 63L, 134L, 77L, 92L, 95L, 32L, 109L, 136L, 
    111L, 158L, 101L, 111L, 178L, 128L, 137L, 198L, 92L, 124L, 
    85L, 68L, 94L, 90L, 132L, 31L, 80L, 110L, 17L, 85L, 172L, 
    164L, 184L, 175L, 147L, 227L, 89L, 108L, 97L, 31L, 79L, 71L, 
    144L, 114L, 16L, 78L, 62L, 124L, 67L, 50L, 64L, 45L, 147L, 
    158L, 96L, 98L, 160L, 106L, 128L, 98L, 115L, 72L, 89L, 64L, 
    141L, 88L, 47L, 122L, 85L, 20L, 111L, 102L, 41L, 157L, 159L, 
    154L, 128L, 159L, 60L, 108L, 131L, 176L, 146L, 14L, 310L, 
    96L, 190L, 128L, 203L, 165L, 204L, 336L, 175L, 216L, 181L, 
    214L, 214L, 201L, 74L, 119L, 181L, 106L, 212L, 147L, 183L, 
    78L, 202L, 225L, 177L, 191L, 162L, 185L, 123L, 173L, 216L, 
    306L, 124L, 237L, 129L, 68L, 213L, 198L, 48L, 169L, 336L, 
    213L, 217L, 132L, 231L, 239L, 116L, 157L, 220L, 181L, 72L, 
    318L, 169L, 78L, 136L, 268L, 162L, 149L, 243L, 135L, 277L, 
    180L, 194L, 136L, 147L, 180L, 44L, 134L, 154L, 118L, 175L, 
    205L, 168L, 249L, 156L, 175L, 113L, 255L, 188L, 127L, 246L, 
    198L, 117L, 199L, 179L, 165L, 145L, 162L, 105L, 140L, 230L, 
    42L, 128L, 65L, 33L, 39L, 304L, 174L, 249L, 174L, 141L, 203L, 
    128L, 159L, 119L, 105L, 94L, 188L, 132L, 197L, 84L, 232L, 
    71L, 167L, 94L, 149L, 147L, 163L, 295L, 226L, 113L, 162L, 
    223L, 127L, 134L, 177L, 206L, 103L, 141L, 197L, 187L, 205L, 
    164L, 181L, 181L, 152L, 152L, 268L, 158L, 134L, 183L, 209L, 
    240L, 298L, 210L, 284L, 189L, 205L, 220L, 171L, 258L, 170L, 
    237L, 311L, 202L, 169L, 273L, 254L, 159L, 289L, 250L, 175L, 
    141L, 251L, 252L, 339L, 203L, 273L, 265L, 244L, 206L, 263L, 
    295L, 160L, 243L, 286L, 278L, 183L, 342L, 368L, 156L, 277L, 
    272L, 205L, 212L, 247L, 208L, 221L, 201L, 249L, 150L, 234L, 
    145L, 217L, 211L, 178L, 171L, 234L, 188L, 262L, 241L, 334L, 
    283L, 270L, 312L, 244L, 268L, 319L, 288L, 162L, 166L, 226L, 
    168L, 256L, 174L, 260L, 242L, 144L, 254L, 192L, 274L, 227L, 
    191L, 293L, 175L, 206L, 175L, 189L, 297L, 253L, 227L, 292L, 
    136L, 185L, 330L, 112L, 208L, 138L, 299L, 149L, 193L, 100L, 
    187L, 142L, 196L, 166L, 235L, 143L, 178L, 305L, 241L, 200L, 
    223L, 161L, 184L, 230L, 194L, 140L, 224L, 286L, 191L, 293L, 
    285L, 219L, 228L, 241L, 244L, 187L, 256L, 308L, 283L, 225L, 
    187L, 233L, 189L, 288L, 298L, 191L, 247L, 303L, 271L, 286L, 
    203L, 307L, 234L, 96L, 171L, 278L, 352L, 194L, 169L, 159L, 
    254L, 240L, 292L, 171L, 299L, 191L, 227L, 206L, 206L, 231L, 
    195L, 186L, 313L, 250L, 166L, 247L, 136L, 196L, 302L, 290L, 
    222L, 229L, 261L, 221L, 198L, 326L, 248L, 207L, 312L, 312L, 
    322L, 361L, 358L, 267L, 255L, 292L, 259L, 293L, 281L, 282L, 
    302L, 238L, 307L, 259L, 307L, 247L, 189L, 292L, 194L, 180L, 
    193L, 264L, 248L, 325L, 264L, 304L, 286L, 357L, 370L, 345L, 
    259L, 264L, 240L, 305L, 184L, 364L, 269L, 222L, 240L, 260L, 
    320L, 286L, 358L, 213L, 319L, 192L, 332L, 216L, 227L, 374L, 
    232L, 257L, 240L, 266L, 282L, 217L, 253L, 153L, 315L, 325L, 
    245L, 130L, 287L, 333L, 296L, 301L, 350L, 93L, 358L, 279L, 
    272L, 253L, 343L, 165L, 232L, 298L, 329L, 320L, 196L, 362L, 
    292L, 298L, 202L, 273L, 251L, 196L, 161L, 347L, 298L, 294L, 
    225L, 157L, 337L, 277L, 321L, 210L, 300L, 232L, 217L, 310L, 
    342L, 155L, 212L, 367L, 269L, 310L, 376L, 288L, 241L, 277L, 
    235L, 304L, 190L, 342L, 339L, 267L, 242L, 252L, 348L, 346L, 
    355L, 156L, 186L, 373L, 240L, 205L, 287L, 265L, 336L, 305L, 
    234L, 348L, 317L, 196L, 290L, 281L, 328L, 220L, 275L, 377L, 
    372L, 351L, 318L, 265L, 260L, 241L, 384L, 359L, 302L, 265L, 
    315L, 274L, 316L, 284L, 216L, 294L, 308L, 262L, 306L, 359L, 
    363L, 133L, 126L, 378L, 351L, 270L, 236L, 386L, 302L, 354L, 
    294L, 325L, 369L, 326L, 333L, 263L, 379L, 216L, 345L, 383L, 
    244L, 345L, 331L, 335L, 360L, 206L, 359L, 330L, 334L, 327L, 
    188L, 309L, 304L, 299L, 295L, 195L, 368L, 341L, 351L, 349L, 
    323L, 261L, 231L, 293L, 288L, 291L, 309L, 151L, 330L, 373L, 
    250L, 366L, 314L, 220L, 279L, 376L, 382L, 333L, 247L, 294L, 
    356L, 374L, 343L, 353L, 341L, 355L, 387L, 228L, 344L, 341L, 
    296L, 294L, 355L, 253L, 292L, 380L, 340L, 375L, 376L, 369L, 
    230L, 350L, 280L, 375L, 374L, 371L, 276L, 295L, 341L, 365L, 
    224L, 312L, 291L, 324L, 307L, 359L, 307L, 269L, 314L, 312L, 
    337L, 367L, 258L, 324L, 317L, 350L, 385L, 360L, 332L, 284L, 
    350L, 351L, 338L, 381L), .Label = c("107.7", "108.7", "108.8", 
    "108.9", "109.7", "109.8", "109.9", "110.6", "110.8", "110.9", 
    "111.4", "111.8", "111.9", "112.0", "112.1", "112.4", "112.5", 
    "112.7", "112.8", "113.0", "113.1", "113.2", "113.5", "113.6", 
    "114.1", "114.3", "114.4", "114.5", "115.1", "115.4", "115.5", 
    "115.6", "115.9", "116.0", "116.1", "116.2", "116.3", "116.5", 
    "116.6", "116.7", "116.8", "116.9", "117.0", "117.1", "117.2", 
    "117.3", "117.4", "117.5", "117.6", "117.7", "117.9", "118.0", 
    "118.1", "118.2", "118.3", "118.6", "118.7", "118.9", "119.0", 
    "119.1", "119.2", "119.3", "119.4", "119.5", "119.6", "119.7", 
    "119.8", "119.9", "120.0", "120.1", "120.3", "120.4", "120.5", 
    "120.6", "120.7", "120.8", "120.9", "121.0", "121.1", "121.2", 
    "121.3", "121.4", "121.5", "121.6", "121.7", "121.8", "121.9", 
    "122.0", "122.1", "122.2", "122.3", "122.4", "122.5", "122.6", 
    "122.7", "122.8", "122.9", "123.0", "123.1", "123.2", "123.3", 
    "123.4", "123.5", "123.6", "123.7", "123.8", "123.9", "124.0", 
    "124.1", "124.2", "124.3", "124.4", "124.5", "124.6", "124.7", 
    "124.9", "125.0", "125.1", "125.2", "125.3", "125.4", "125.5", 
    "125.6", "125.7", "125.8", "126.0", "126.3", "126.4", "126.7", 
    "126.8", "126.9", "127.1", "127.2", "127.3", "127.4", "127.5", 
    "127.6", "127.7", "127.8", "127.9", "128.0", "128.1", "128.2", 
    "128.3", "128.4", "128.5", "128.6", "128.7", "128.8", "128.9", 
    "129.0", "129.1", "129.2", "129.3", "129.4", "129.5", "129.6", 
    "129.7", "129.8", "129.9", "130.0", "130.1", "130.2", "130.3", 
    "130.4", "130.5", "130.6", "130.7", "130.8", "130.9", "131.0", 
    "131.1", "131.2", "131.3", "131.4", "131.5", "131.6", "131.7", 
    "131.8", "131.9", "132.0", "132.1", "132.2", "132.3", "132.4", 
    "132.5", "132.6", "132.7", "132.8", "133.0", "133.1", "133.2", 
    "133.3", "133.4", "133.6", "133.7", "133.8", "133.9", "134.0", 
    "134.1", "134.2", "134.3", "134.4", "134.5", "134.6", "134.7", 
    "134.8", "134.9", "135.1", "135.2", "135.3", "135.4", "135.5", 
    "135.6", "135.7", "135.9", "136.0", "136.1", "136.2", "136.3", 
    "136.4", "136.5", "136.6", "136.7", "136.8", "136.9", "137.0", 
    "137.2", "137.3", "137.4", "137.5", "137.6", "137.7", "137.8", 
    "137.9", "138.0", "138.1", "138.2", "138.3", "138.4", "138.6", 
    "138.7", "138.8", "138.9", "139.0", "139.1", "139.2", "139.3", 
    "139.4", "139.5", "139.6", "139.7", "139.8", "140.0", "140.1", 
    "140.2", "140.4", "140.5", "140.6", "140.7", "140.8", "140.9", 
    "141.0", "141.2", "141.4", "141.5", "141.6", "141.7", "141.8", 
    "141.9", "142.0", "142.1", "142.2", "142.3", "142.4", "142.5", 
    "142.8", "142.9", "143.0", "143.1", "143.2", "143.3", "143.4", 
    "143.5", "143.6", "143.8", "143.9", "144.0", "144.1", "144.2", 
    "144.3", "144.4", "144.5", "144.6", "144.7", "144.8", "144.9", 
    "145.0", "145.1", "145.2", "145.4", "145.5", "145.6", "145.7", 
    "145.9", "146.0", "146.1", "146.2", "146.3", "146.4", "146.5", 
    "146.6", "146.7", "146.8", "146.9", "147.0", "147.1", "147.2", 
    "147.4", "147.6", "147.7", "147.8", "147.9", "148.0", "148.1", 
    "148.2", "148.3", "148.4", "148.5", "148.7", "148.8", "148.9", 
    "149.0", "149.1", "149.2", "149.4", "149.5", "149.6", "149.7", 
    "149.8", "149.9", "150.0", "150.2", "150.3", "150.5", "150.6", 
    "150.7", "150.9", "151.0", "151.4", "151.5", "151.6", "151.7", 
    "152.0", "152.2", "152.3", "152.4", "152.6", "152.7", "152.8", 
    "152.9", "153.1", "153.4", "153.5", "153.7", "153.8", "154.0", 
    "154.1", "154.9", "155.0", "155.1", "155.2", "155.3", "155.4", 
    "155.5", "155.7", "155.8", "156.3", "156.4", "156.6", "156.7", 
    "157.0", "157.1", "157.2", "158.9", "161.1", "164.1", "Height"
    ), class = "factor")), class = "data.frame", row.names = c(NA, 
-906L))
..hiv <-
structure(list(V1 = structure(c(70L, 36L, 69L, 24L, 10L, 3L, 
3L, 12L, 35L, 20L, 23L, 61L, 45L, 25L, 27L, 40L, 30L, 52L, 31L, 
32L, 44L, 64L, 50L, 37L, 62L, 66L, 67L, 60L, 41L, 50L, 19L, 59L, 
33L, 47L, 49L, 39L, 56L, 36L, 42L, 48L, 53L, 58L, 21L, 20L, 38L, 
43L, 26L, 11L, 32L, 7L, 4L, 14L, 34L, 17L, 45L, 28L, 57L, 46L, 
65L, 68L, 63L, 51L, 54L, 55L, 29L, 5L, 1L, 15L, 18L, 13L, 9L, 
8L, 2L, 16L, 22L, 6L), .Label = c("0.416", "0.786", "0.788", 
"0.799", "0.801", "0.844", "0.847", "0.871", "0.873", "0.881", 
"0.894", "0.896", "0.899", "0.918", "0.929", "0.93", "0.943", 
"0.95", "0.959", "0.963", "0.966", "0.968", "0.971", "0.977", 
"0.984", "0.985", "0.986", "0.988", "0.99", "0.996", "1.016", 
"1.019", "1.027", "1.033", "1.038", "1.053", "1.054", "1.064", 
"1.066", "1.067", "1.079", "1.082", "1.086", "1.088", "1.089", 
"1.106", "1.109", "1.113", "1.118", "1.12", "1.128", "1.129", 
"1.14", "1.141", "1.144", "1.146", "1.169", "1.172", "1.229", 
"1.233", "1.234", "1.235", "1.271", "1.28", "1.308", "1.327", 
"1.361", "1.498", "1.708", "Absorbance"), class = "factor"), 
    V2 = structure(c(6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L), .Label = c("1", "2", "3", "4", "5", 
    "Lot"), class = "factor"), V3 = structure(c(6L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 
    2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L), .Label = c("1", 
    "2", "3", "4", "5", "Run"), class = "factor")), class = "data.frame", row.names = c(NA, 
-76L))
..hoop <-
structure(list(V1 = structure(c(6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("-20", 
"0", "20", "40", "60", "Temp"), class = "factor"), V2 = structure(c(11L, 
1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 2L, 1L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 2L, 1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 2L, 
1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 2L, 1L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 2L), .Label = c("1", "10", "2", "3", "4", "5", 
"6", "7", "8", "9", "Tree"), class = "factor"), V3 = structure(c(50L, 
11L, 27L, 14L, 25L, 26L, 23L, 20L, 21L, 28L, 24L, 10L, 19L, 9L, 
17L, 12L, 16L, 13L, 15L, 22L, 18L, 47L, 7L, 49L, 2L, 1L, 3L, 
5L, 4L, 8L, 6L, 39L, 48L, 41L, 43L, 45L, 45L, 42L, 44L, 46L, 
40L, 33L, 38L, 34L, 37L, 36L, 35L, 30L, 29L, 31L, 32L), .Label = c("10.29", 
"10.33", "10.35", "10.46", "10.56", "10.74", "11.3", "11.94", 
"12.32", "12.46", "13.14", "13.16", "13.25", "13.39", "13.54", 
"13.64", "13.68", "14.06", "14.11", "15.06", "15.21", "15.23", 
"15.26", "15.45", "15.51", "15.53", "15.9", "16.9", "6.09", "6.15", 
"6.26", "6.29", "6.34", "6.41", "6.62", "6.68", "7.06", "7.27", 
"7.63", "7.75", "7.9", "8.1", "8.27", "8.3", "8.67", "9.34", 
"9.43", "9.56", "9.65", "Strength"), class = "factor"), V4 = structure(c(34L, 
32L, 25L, 26L, 25L, 25L, 31L, 22L, 14L, 13L, 5L, 26L, 15L, 20L, 
17L, 27L, 18L, 11L, 9L, 7L, 2L, 33L, 21L, 23L, 22L, 16L, 21L, 
1L, 4L, 7L, 3L, 28L, 8L, 29L, 17L, 11L, 24L, 19L, 23L, 15L, 10L, 
12L, 3L, 16L, 14L, 11L, 27L, 28L, 30L, 29L, 6L), .Label = c("34.9", 
"35.7", "36.7", "37.5", "37.7", "38.2", "38.5", "38.6", "38.8", 
"38.9", "39", "39.1", "39.2", "39.3", "39.4", "39.7", "39.8", 
"40", "40.1", "40.2", "40.3", "40.4", "40.6", "40.9", "41", "41.1", 
"41.2", "41.4", "41.7", "41.8", "42", "42.1", "43.1", "Moisture"
), class = "factor")), class = "data.frame", row.names = c(NA, 
-51L))
..imf2015 <-
structure(list(V1 = structure(c(5L, 1L, 2L, 3L, 4L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L
), .Label = c("Australia", "Austria", "Belgium", "Canada", "Country", 
"Cyprus", "CzechRepublic", "Denmark", "Estonia", "Finland", "France", 
"Germany", "Greece", "Iceland", "Ireland", "Israel", "Italy", 
"Japan", "Korea", "Latvia", "Lithuania", "Luxembourg", "Netherlands", 
"NewZealand", "Norway", "Portugal", "Singapore", "SlovakRepublic", 
"Slovenia", "Spain", "Sweden", "Switzerland", "UnitedKingdom", 
"UnitedStates"), class = "factor"), V2 = structure(c(34L, 10L, 
18L, 14L, 8L, 6L, 15L, 33L, 22L, 2L, 1L, 30L, 12L, 28L, 19L, 
24L, 17L, 23L, 29L, 3L, 4L, 27L, 32L, 7L, 31L, 11L, 21L, 13L, 
26L, 16L, 25L, 20L, 9L, 5L), .Label = c("-0.2", "-0.416", "-0.775", 
"-2.335", "-2.567", "-2.914", "-3.363", "-3.401", "-4.284", "-4.732", 
"0.069", "0.117", "0.213", "0.442", "0.908", "1.369", "1.62", 
"1.846", "10.241", "11.525", "18.11", "2.206", "3.094", "4.348", 
"4.695", "5.18", "5.241", "5.471", "7.661", "8.328", "8.661", 
"8.676", "9.155", "CAB"), class = "factor"), V3 = structure(c(34L, 
14L, 29L, 4L, 31L, 5L, 17L, 16L, 1L, 22L, 32L, 26L, 8L, 25L, 
27L, 23L, 7L, 10L, 15L, 13L, 18L, 9L, 24L, 11L, 12L, 6L, 2L, 
21L, 28L, 33L, 19L, 20L, 30L, 3L), .Label = c("10.052", "103.239", 
"105.607", "105.761", "107.533", "128.988", "132.042", "179.354", 
"22.091", "237.968", "29.557", "33.203", "34.837", "37.626", 
"37.755", "39.554", "40.314", "42.544", "42.926", "45.802", "52.495", 
"63.663", "64.082", "65.119", "68.05", "71.151", "78.706", "83.149", 
"85.544", "88.96", "91.55", "96.164", "99.772", "DEBT"), class = "factor"), 
    V4 = structure(c(34L, 9L, 29L, 30L, 13L, 15L, 16L, 31L, 14L, 
    32L, 33L, 20L, 28L, 18L, 3L, 11L, 27L, 8L, 2L, 10L, 6L, 17L, 
    22L, 5L, 24L, 25L, 1L, 23L, 21L, 19L, 26L, 4L, 12L, 7L), .Label = c("18.316", 
    "20.923", "29.473", "32.65", "34.227", "34.413", "35.284", 
    "36.638", "37.269", "37.705", "39.622", "40.129", "40.251", 
    "40.365", "40.391", "41.975", "42.119", "42.882", "43.76", 
    "43.981", "44.083", "45.195", "45.272", "47.974", "48.36", 
    "48.919", "50.449", "51.199", "51.607", "53.861", "54.825", 
    "56.979", "56.981", "EXP"), class = "factor"), V5 = structure(c(34L, 
    27L, 22L, 18L, 21L, 10L, 6L, 28L, 5L, 20L, 17L, 19L, 7L, 
    26L, 31L, 15L, 13L, 14L, 12L, 2L, 3L, 1L, 24L, 16L, 32L, 
    8L, 29L, 4L, 9L, 11L, 25L, 33L, 23L, 30L), .Label = c("100950.492", 
    "13614.467", "14259.6", "16105.126", "17111.301", "17569.893", 
    "17955.191", "19225.674", "20746.898", "23105.397", "25717.563", 
    "27105.076", "30032.106", "34513.355", "35743.461", "37281.09", 
    "37612.91", "40520.104", "41197.411", "42487.05", "43349.618", 
    "43749.552", "43976.416", "44322.826", "50319.105", "50472.936", 
    "51363.897", "53237.279", "53628.762", "56174.941", "60896.183", 
    "74264.426", "81410.024", "GDP"), class = "factor"), V6 = structure(c(34L, 
    31L, 29L, 25L, 30L, 11L, 22L, 23L, 14L, 2L, 15L, 18L, 9L, 
    32L, 1L, 7L, 16L, 28L, 27L, 19L, 8L, 13L, 20L, 21L, 33L, 
    24L, 5L, 3L, 6L, 4L, 26L, 10L, 12L, 17L), .Label = c("-0.017", 
    "-0.156", "-0.336", "-0.497", "-0.523", "-0.526", "-0.632", 
    "-0.677", "-1.094", "-1.14", "-1.539", "0.05", "0.061", "0.068", 
    "0.09", "0.108", "0.12", "0.134", "0.213", "0.22", "0.293", 
    "0.335", "0.452", "0.508", "0.62", "0.702", "0.706", "0.793", 
    "0.81", "1.132", "1.461", "1.633", "2.171", "INFL"), class = "factor"), 
    V7 = structure(c(34L, 28L, 23L, 22L, 24L, 1L, 30L, 9L, 27L, 
    15L, 18L, 6L, 33L, 5L, 16L, 11L, 4L, 25L, 32L, 17L, 10L, 
    8L, 7L, 19L, 31L, 2L, 29L, 21L, 13L, 12L, 26L, 20L, 3L, 14L
    ), .Label = c("13.956", "15.451", "17.18", "17.314", "19.081", 
    "19.243", "19.272", "19.625", "19.755", "19.89", "19.948", 
    "20.06", "20.064", "20.348", "21.144", "21.763", "22.091", 
    "22.363", "22.747", "22.995", "23.202", "23.211", "23.507", 
    "23.817", "23.896", "24.207", "24.745", "26.304", "26.77", 
    "27.357", "28.208", "28.918", "9.829", "INV"), class = "factor"), 
    V8 = structure(c(34L, 21L, 20L, 28L, 26L, 6L, 15L, 23L, 22L, 
    31L, 2L, 14L, 8L, 12L, 32L, 17L, 4L, 10L, 11L, 33L, 30L, 
    24L, 25L, 18L, 13L, 5L, 1L, 3L, 29L, 7L, 27L, 9L, 19L, 16L
    ), .Label = c("1.9", "10.367", "11.492", "11.908", "12.444", 
    "14.892", "22.058", "24.9", "3.178", "3.375", "3.642", "3.992", 
    "4.374", "4.608", "5.046", "5.258", "5.275", "5.35", "5.4", 
    "5.75", "6.058", "6.104", "6.192", "6.804", "6.891", "6.9", 
    "7.4", "8.492", "9", "9.119", "9.375", "9.442", "9.877", 
    "UNMP"), class = "factor")), class = "data.frame", row.names = c(NA, 
-34L))
..Iris <-
structure(list(V1 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("1", 
"2", "3", "Species_No"), class = "factor"), V2 = structure(c(23L, 
12L, 12L, 12L, 1L, 12L, 12L, 12L, 20L, 12L, 12L, 20L, 12L, 12L, 
1L, 19L, 20L, 12L, 12L, 12L, 12L, 1L, 12L, 20L, 1L, 12L, 20L, 
12L, 12L, 1L, 12L, 20L, 19L, 19L, 12L, 19L, 21L, 12L, 22L, 19L, 
12L, 12L, 12L, 20L, 12L, 12L, 19L, 19L, 12L, 12L, 12L, 5L, 8L, 
6L, 4L, 2L, 2L, 7L, 2L, 6L, 4L, 7L, 5L, 7L, 3L, 5L, 6L, 9L, 7L, 
6L, 3L, 7L, 7L, 6L, 2L, 5L, 5L, 8L, 2L, 5L, 2L, 4L, 5L, 7L, 5L, 
6L, 7L, 10L, 8L, 5L, 3L, 4L, 7L, 4L, 5L, 2L, 7L, 5L, 5L, 6L, 
5L, 17L, 16L, 13L, 11L, 9L, 11L, 10L, 14L, 11L, 10L, 7L, 16L, 
13L, 10L, 14L, 18L, 14L, 15L, 7L, 16L, 16L, 18L, 10L, 16L, 14L, 
10L, 10L, 16L, 10L, 13L, 18L, 10L, 15L, 14L, 5L, 13L, 13L, 6L, 
10L, 17L, 8L, 14L, 10L, 16L, 11L, 10L, 15L, 11L, 13L, 17L), .Label = c("1", 
"10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "2", 
"20", "21", "22", "23", "24", "25", "3", "4", "5", "6", "Petal_width"
), class = "factor"), V3 = structure(c(44L, 5L, 1L, 7L, 5L, 4L, 
7L, 7L, 9L, 5L, 5L, 6L, 5L, 5L, 5L, 8L, 6L, 4L, 4L, 7L, 3L, 2L, 
5L, 7L, 6L, 6L, 8L, 4L, 6L, 6L, 6L, 4L, 4L, 6L, 6L, 5L, 8L, 5L, 
7L, 5L, 9L, 3L, 5L, 6L, 6L, 6L, 4L, 5L, 7L, 8L, 6L, 22L, 24L, 
24L, 17L, 11L, 18L, 22L, 11L, 16L, 16L, 19L, 21L, 26L, 10L, 13L, 
21L, 27L, 22L, 23L, 16L, 22L, 22L, 21L, 12L, 19L, 19L, 22L, 12L, 
31L, 27L, 24L, 18L, 26L, 17L, 25L, 23L, 25L, 28L, 17L, 15L, 21L, 
22L, 19L, 33L, 14L, 24L, 18L, 20L, 24L, 17L, 33L, 28L, 29L, 28L, 
22L, 27L, 26L, 33L, 28L, 32L, 27L, 34L, 26L, 35L, 31L, 38L, 32L, 
33L, 28L, 36L, 31L, 34L, 28L, 30L, 34L, 37L, 26L, 38L, 25L, 28L, 
37L, 32L, 42L, 41L, 29L, 40L, 42L, 33L, 25L, 33L, 35L, 36L, 33L, 
43L, 38L, 39L, 35L, 30L, 27L, 28L), .Label = c("10", "11", "12", 
"13", "14", "15", "16", "17", "19", "30", "33", "35", "36", "37", 
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", 
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", 
"60", "61", "63", "64", "66", "67", "69", "Petal_length"), class = "factor"), 
    V4 = structure(c(24L, 13L, 16L, 11L, 16L, 12L, 18L, 10L, 
    18L, 10L, 16L, 14L, 22L, 9L, 10L, 18L, 17L, 15L, 10L, 12L, 
    12L, 10L, 15L, 14L, 21L, 11L, 19L, 12L, 14L, 11L, 17L, 19L, 
    3L, 18L, 15L, 14L, 13L, 14L, 15L, 10L, 14L, 20L, 12L, 23L, 
    14L, 11L, 15L, 15L, 14L, 14L, 17L, 8L, 13L, 12L, 6L, 3L, 
    7L, 9L, 4L, 7L, 7L, 10L, 3L, 5L, 5L, 9L, 10L, 10L, 2L, 10L, 
    5L, 12L, 10L, 11L, 6L, 6L, 7L, 14L, 1L, 9L, 2L, 8L, 8L, 11L, 
    5L, 8L, 8L, 12L, 7L, 8L, 4L, 6L, 10L, 10L, 9L, 4L, 11L, 10L, 
    9L, 9L, 3L, 11L, 11L, 10L, 7L, 5L, 5L, 7L, 8L, 7L, 11L, 2L, 
    12L, 8L, 5L, 11L, 16L, 10L, 8L, 8L, 12L, 14L, 13L, 10L, 12L, 
    13L, 12L, 10L, 10L, 10L, 12L, 13L, 10L, 18L, 10L, 10L, 18L, 
    8L, 6L, 8L, 14L, 10L, 10L, 9L, 6L, 8L, 9L, 10L, 7L, 5L, 8L
    ), .Label = c("20", "22", "23", "24", "25", "26", "27", "28", 
    "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", 
    "39", "40", "41", "42", "44", "Sepal_width"), class = "factor"), 
    V5 = structure(c(36L, 8L, 4L, 6L, 7L, 2L, 9L, 8L, 9L, 7L, 
    8L, 12L, 13L, 2L, 6L, 15L, 9L, 13L, 2L, 5L, 8L, 1L, 9L, 8L, 
    10L, 7L, 12L, 5L, 9L, 7L, 12L, 12L, 3L, 9L, 10L, 4L, 9L, 
    10L, 8L, 6L, 6L, 16L, 4L, 15L, 10L, 4L, 8L, 9L, 6L, 12L, 
    11L, 15L, 21L, 28L, 16L, 8L, 16L, 18L, 7L, 10L, 16L, 17L, 
    21L, 21L, 9L, 14L, 24L, 25L, 20L, 19L, 14L, 22L, 12L, 25L, 
    15L, 15L, 14L, 18L, 8L, 20L, 18L, 19L, 15L, 27L, 13L, 26L, 
    23L, 17L, 18L, 19L, 13L, 13L, 14L, 15L, 24L, 13L, 25L, 14L, 
    22L, 19L, 13L, 25L, 27L, 23L, 16L, 7L, 21L, 21L, 22L, 16L, 
    22L, 18L, 27L, 14L, 25L, 27L, 30L, 26L, 22L, 21L, 26L, 20L, 
    25L, 17L, 22L, 25L, 30L, 19L, 34L, 18L, 23L, 21L, 23L, 34L, 
    33L, 25L, 35L, 34L, 19L, 20L, 21L, 30L, 29L, 21L, 34L, 32L, 
    31L, 23L, 22L, 15L, 16L), .Label = c("43", "44", "45", "46", 
    "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", 
    "57", "58", "59", "60", "61", "62", "63", "64", "65", "66", 
    "67", "68", "69", "70", "71", "72", "73", "74", "76", "77", 
    "79", "Sepal_length"), class = "factor"), V6 = structure(c(2L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L
    ), .Label = c("Setosa", "Species_name", "Verginica", "Versicolor"
    ), class = "factor")), class = "data.frame", row.names = c(NA, 
-151L))
..kinks <-
structure(list(V1 = structure(c(38L, 20L, 26L, 18L, 17L, 34L, 
23L, 22L, 21L, 20L, 23L, 16L, 22L, 15L, 18L, 21L, 9L, 15L, 20L, 
19L, 16L, 19L, 31L, 32L, 25L, 24L, 35L, 36L, 33L, 37L, 33L, 22L, 
27L, 9L, 5L, 8L, 29L, 13L, 29L, 24L, 27L, 37L, 12L, 15L, 19L, 
16L, 9L, 16L, 10L, 12L, 19L, 2L, 13L, 14L, 17L, 16L, 8L, 8L, 
11L, 8L, 1L, 30L, 10L, 19L, 17L, 12L, 21L, 16L, 14L, 22L, 18L, 
20L, 9L, 3L, 6L, 16L, 18L, 7L, 10L, 4L, 19L, 8L, 34L, 27L, 31L, 
23L, 28L, 31L, 19L, 29L, 24L, 21L, 33L, 29L, 32L, 33L, 27L, 29L, 
29L, 27L, 28L), .Label = c("16", "25", "28", "32", "34", "35", 
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", 
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", 
"60", "61", "62", "63", "64", "65", "66", "67", "68", "beta"), class = "factor"), 
    V2 = structure(c(5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L), .Label = c("1", "2", "3", "4", "order"), class = "factor"), 
    V3 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L), .Label = c("1", "2", "3", "type"), class = "factor")), class = "data.frame", row.names = c(NA, 
-101L))
..LAcrimeTemp <-
structure(list(V1 = structure(c(20L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 
18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 19L, 
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L), .Label = c("1975", "1976", 
"1977", "1978", "1979", "1980", "1981", "1982", "1983", "1984", 
"1985", "1986", "1987", "1988", "1989", "1990", "1991", "1992", 
"1993", "Year"), class = "factor"), V2 = structure(c(13L, 1L, 
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 
1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 
7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 
4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 
4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 2L, 3L, 4L, 1L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 2L, 3L, 4L), .Label = c("1", "10", "11", "12", "2", "3", 
"4", "5", "6", "7", "8", "9", "Month"), class = "factor"), V3 = structure(c(20L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 
16L, 16L, 16L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 
18L, 18L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 
19L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L
), .Label = c("2729878", "2739100", "2785393", "2787525", "2863412", 
"2952511", "3031090", "3101979", "3144256", "3158688", "3186459", 
"3260856", "3341726", "3402342", "3441449", "3485398", "3525317", 
"3558316", "3615355", "Population"), class = "factor"), V4 = structure(c(98L, 
16L, 9L, 10L, 15L, 40L, 54L, 75L, 72L, 82L, 59L, 37L, 21L, 34L, 
22L, 25L, 22L, 50L, 71L, 82L, 77L, 83L, 77L, 61L, 34L, 20L, 37L, 
11L, 40L, 40L, 57L, 73L, 85L, 74L, 63L, 55L, 39L, 26L, 24L, 44L, 
29L, 59L, 69L, 69L, 80L, 95L, 72L, 28L, 3L, 4L, 2L, 20L, 35L, 
51L, 77L, 72L, 86L, 96L, 62L, 40L, 37L, 32L, 41L, 24L, 37L, 34L, 
60L, 74L, 85L, 65L, 63L, 46L, 35L, 31L, 37L, 23L, 40L, 55L, 91L, 
90L, 87L, 79L, 58L, 44L, 30L, 4L, 29L, 20L, 35L, 46L, 51L, 77L, 
88L, 89L, 77L, 40L, 13L, 27L, 19L, 21L, 29L, 46L, 59L, 79L, 95L, 
92L, 78L, 39L, 17L, 24L, 25L, 41L, 41L, 62L, 66L, 87L, 94L, 97L, 
60L, 26L, 7L, 9L, 15L, 7L, 37L, 40L, 62L, 88L, 81L, 74L, 66L, 
26L, 29L, 45L, 26L, 29L, 42L, 50L, 64L, 73L, 75L, 61L, 64L, 56L, 
25L, 6L, 24L, 27L, 49L, 53L, 55L, 64L, 69L, 79L, 76L, 43L, 1L, 
15L, 37L, 46L, 41L, 48L, 51L, 77L, 72L, 69L, 62L, 34L, 14L, 8L, 
5L, 27L, 55L, 46L, 57L, 78L, 69L, 72L, 61L, 57L, 36L, 17L, 6L, 
20L, 46L, 47L, 68L, 88L, 79L, 86L, 79L, 53L, 16L, 18L, 33L, 6L, 
39L, 35L, 52L, 65L, 76L, 70L, 67L, 50L, 26L, 25L, 38L, 29L, 60L, 
62L, 61L, 88L, 93L, 84L, 65L, 51L, 10L, 12L, 17L, 36L, 47L, 57L, 
72L, 78L, 78L, 76L, 72L, 51L, 25L), .Label = c("12.2", "12.3", 
"12.4", "12.6", "12.7", "12.8", "12.9", "13", "13.1", "13.2", 
"13.3", "13.4", "13.5", "13.6", "13.7", "13.8", "13.9", "14", 
"14.1", "14.2", "14.3", "14.4", "14.5", "14.6", "14.7", "14.8", 
"14.9", "15", "15.1", "15.2", "15.3", "15.4", "15.5", "15.6", 
"15.7", "15.8", "15.9", "16", "16.1", "16.2", "16.3", "16.5", 
"16.6", "16.7", "16.8", "16.9", "17.1", "17.2", "17.3", "17.4", 
"17.6", "17.7", "17.9", "18.1", "18.2", "18.3", "18.4", "18.5", 
"18.6", "18.7", "18.8", "18.9", "19", "19.1", "19.4", "19.5", 
"19.6", "19.7", "19.8", "19.9", "20", "20.2", "20.3", "20.4", 
"20.5", "20.6", "20.7", "20.8", "20.9", "21", "21.1", "21.2", 
"21.3", "21.5", "21.6", "21.7", "21.8", "21.9", "22", "22.1", 
"22.2", "22.4", "22.7", "22.8", "23.1", "23.2", "24.7", "TempCelsius"
), class = "factor"), V5 = structure(c(98L, 16L, 9L, 10L, 15L, 
40L, 54L, 75L, 72L, 82L, 59L, 37L, 21L, 34L, 22L, 25L, 22L, 50L, 
71L, 82L, 77L, 83L, 77L, 61L, 34L, 20L, 37L, 11L, 40L, 40L, 57L, 
73L, 85L, 74L, 63L, 55L, 39L, 26L, 24L, 44L, 29L, 59L, 69L, 69L, 
80L, 95L, 72L, 28L, 3L, 4L, 2L, 20L, 35L, 51L, 77L, 72L, 86L, 
96L, 62L, 40L, 37L, 32L, 41L, 24L, 37L, 34L, 60L, 74L, 85L, 65L, 
63L, 46L, 35L, 31L, 37L, 23L, 40L, 55L, 91L, 90L, 87L, 79L, 58L, 
44L, 30L, 4L, 29L, 20L, 35L, 46L, 51L, 77L, 88L, 89L, 77L, 40L, 
13L, 27L, 19L, 21L, 29L, 46L, 59L, 79L, 95L, 92L, 78L, 39L, 17L, 
24L, 25L, 41L, 41L, 62L, 66L, 87L, 94L, 97L, 60L, 26L, 7L, 9L, 
15L, 7L, 37L, 40L, 62L, 88L, 81L, 74L, 66L, 26L, 29L, 45L, 26L, 
29L, 42L, 50L, 64L, 73L, 75L, 61L, 64L, 56L, 25L, 6L, 24L, 27L, 
49L, 53L, 55L, 64L, 69L, 79L, 76L, 43L, 1L, 15L, 37L, 46L, 41L, 
48L, 51L, 77L, 72L, 69L, 62L, 34L, 14L, 8L, 5L, 27L, 55L, 46L, 
57L, 78L, 69L, 72L, 61L, 57L, 36L, 17L, 6L, 20L, 46L, 47L, 68L, 
88L, 79L, 86L, 79L, 53L, 16L, 18L, 33L, 6L, 39L, 35L, 52L, 65L, 
76L, 70L, 67L, 50L, 26L, 25L, 38L, 29L, 60L, 62L, 61L, 88L, 93L, 
84L, 65L, 51L, 10L, 12L, 17L, 36L, 47L, 57L, 72L, 78L, 78L, 76L, 
72L, 51L, 25L), .Label = c("53.96", "54.14", "54.32", "54.68", 
"54.86", "55.04", "55.22", "55.4", "55.58", "55.76", "55.94", 
"56.12", "56.3", "56.48", "56.66", "56.84", "57.02", "57.2", 
"57.38", "57.56", "57.74", "57.92", "58.1", "58.28", "58.46", 
"58.64", "58.82", "59", "59.18", "59.36", "59.54", "59.72", "59.9", 
"60.08", "60.26", "60.44", "60.62", "60.8", "60.98", "61.16", 
"61.34", "61.7", "61.88", "62.06", "62.24", "62.42", "62.78", 
"62.96", "63.14", "63.32", "63.68", "63.86", "64.22", "64.58", 
"64.76", "64.94", "65.12", "65.3", "65.48", "65.66", "65.84", 
"66.02", "66.2", "66.38", "66.92", "67.1", "67.28", "67.46", 
"67.64", "67.82", "68", "68.36", "68.54", "68.72", "68.9", "69.08", 
"69.26", "69.44", "69.62", "69.8", "69.98", "70.16", "70.34", 
"70.7", "70.88", "71.06", "71.24", "71.42", "71.6", "71.78", 
"71.96", "72.32", "72.86", "73.04", "73.58", "73.76", "76.46", 
"Fahrenheit"), class = "factor"), V6 = structure(c(70L, 26L, 
20L, 25L, 14L, 20L, 16L, 25L, 22L, 23L, 32L, 24L, 23L, 25L, 13L, 
17L, 12L, 26L, 22L, 10L, 21L, 20L, 19L, 18L, 26L, 27L, 18L, 16L, 
36L, 12L, 30L, 17L, 21L, 25L, 15L, 35L, 45L, 11L, 13L, 38L, 18L, 
26L, 27L, 26L, 37L, 46L, 26L, 63L, 29L, 35L, 30L, 34L, 31L, 44L, 
34L, 31L, 50L, 32L, 52L, 44L, 66L, 42L, 37L, 33L, 56L, 43L, 67L, 
67L, 9L, 69L, 60L, 59L, 65L, 36L, 47L, 39L, 43L, 42L, 53L, 67L, 
56L, 47L, 58L, 40L, 46L, 47L, 23L, 57L, 45L, 47L, 46L, 44L, 44L, 
1L, 40L, 33L, 48L, 50L, 21L, 40L, 52L, 56L, 29L, 39L, 46L, 40L, 
53L, 54L, 40L, 44L, 25L, 32L, 38L, 43L, 29L, 37L, 55L, 46L, 43L, 
44L, 24L, 29L, 52L, 46L, 33L, 40L, 26L, 47L, 52L, 32L, 31L, 42L, 
47L, 34L, 30L, 55L, 47L, 37L, 32L, 48L, 59L, 63L, 46L, 42L, 37L, 
44L, 40L, 46L, 52L, 34L, 37L, 37L, 43L, 45L, 42L, 41L, 50L, 39L, 
30L, 28L, 30L, 32L, 26L, 53L, 40L, 49L, 44L, 28L, 37L, 59L, 38L, 
39L, 36L, 38L, 53L, 45L, 48L, 67L, 49L, 38L, 62L, 53L, 54L, 46L, 
53L, 44L, 45L, 6L, 7L, 64L, 62L, 37L, 47L, 46L, 24L, 47L, 60L, 
50L, 5L, 69L, 9L, 68L, 60L, 47L, 69L, 51L, 49L, 56L, 69L, 44L, 
47L, 7L, 8L, 3L, 1L, 69L, 63L, 66L, 54L, 61L, 51L, 67L, 2L, 4L, 
66L, 64L, 64L, 67L, 42L), .Label = c("100", "101", "103", "104", 
"105", "109", "115", "119", "122", "28", "32", "33", "34", "35", 
"36", "37", "38", "40", "42", "44", "45", "46", "47", "48", "49", 
"51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", 
"62", "63", "64", "65", "66", "67", "68", "69", "70", "71", "72", 
"73", "74", "75", "76", "77", "78", "79", "81", "82", "83", "84", 
"85", "86", "87", "88", "90", "92", "93", "94", "95", "96", "97", 
"Homicide"), class = "factor"), V7 = structure(c(108L, 15L, 27L, 
12L, 17L, 39L, 28L, 43L, 3L, 4L, 26L, 17L, 26L, 56L, 6L, 13L, 
34L, 37L, 21L, 91L, 70L, 42L, 65L, 43L, 17L, 38L, 64L, 58L, 63L, 
48L, 58L, 70L, 60L, 34L, 70L, 100L, 73L, 30L, 66L, 67L, 70L, 
85L, 73L, 81L, 56L, 99L, 94L, 72L, 56L, 66L, 38L, 67L, 59L, 59L, 
78L, 75L, 96L, 73L, 83L, 99L, 92L, 96L, 96L, 87L, 93L, 67L, 91L, 
89L, 105L, 95L, 101L, 96L, 76L, 81L, 58L, 52L, 65L, 90L, 93L, 
97L, 102L, 79L, 103L, 82L, 92L, 76L, 45L, 99L, 83L, 104L, 69L, 
93L, 106L, 91L, 88L, 61L, 91L, 63L, 60L, 72L, 80L, 66L, 59L, 
83L, 98L, 86L, 91L, 45L, 75L, 51L, 44L, 53L, 40L, 82L, 63L, 77L, 
102L, 80L, 52L, 62L, 33L, 48L, 16L, 72L, 81L, 64L, 45L, 84L, 
76L, 74L, 43L, 60L, 71L, 57L, 20L, 55L, 18L, 41L, 55L, 36L, 107L, 
63L, 77L, 68L, 40L, 72L, 53L, 74L, 51L, 64L, 63L, 41L, 28L, 56L, 
51L, 26L, 19L, 42L, 9L, 31L, 28L, 59L, 54L, 75L, 53L, 28L, 43L, 
21L, 13L, 39L, 24L, 32L, 49L, 52L, 25L, 46L, 15L, 35L, 31L, 62L, 
38L, 13L, 7L, 23L, 38L, 57L, 59L, 56L, 64L, 46L, 59L, 29L, 10L, 
12L, 11L, 26L, 53L, 30L, 44L, 64L, 30L, 57L, 60L, 21L, 13L, 35L, 
14L, 54L, 43L, 24L, 19L, 46L, 47L, 43L, 12L, 5L, 3L, 8L, 1L, 
20L, 22L, 37L, 38L, 38L, 33L, 15L, 50L, 2L, 5L), .Label = c("118", 
"121", "124", "126", "127", "129", "130", "131", "134", "135", 
"136", "137", "138", "139", "140", "141", "142", "143", "144", 
"145", "147", "149", "150", "151", "152", "153", "154", "156", 
"157", "158", "159", "160", "161", "162", "163", "164", "166", 
"167", "168", "170", "171", "172", "173", "174", "175", "177", 
"178", "179", "180", "181", "183", "184", "185", "186", "187", 
"189", "190", "191", "192", "193", "194", "195", "196", "197", 
"198", "199", "200", "201", "202", "203", "204", "205", "206", 
"207", "208", "209", "211", "213", "214", "215", "216", "217", 
"218", "219", "221", "223", "224", "225", "226", "227", "228", 
"230", "235", "237", "238", "239", "241", "242", "244", "251", 
"254", "256", "257", "264", "282", "284", "365", "Rape"), class = "factor")), class = "data.frame", row.names = c(NA, 
-229L))
..leprosy <-
structure(list(V1 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("A", "D", "F", "treatment"
), class = "factor"), V2 = structure(c(17L, 2L, 15L, 12L, 5L, 
9L, 13L, 1L, 13L, 2L, 11L, 13L, 13L, 14L, 15L, 8L, 15L, 9L, 15L, 
12L, 6L, 7L, 4L, 2L, 16L, 10L, 7L, 3L, 3L, 14L, 3L), .Label = c("10", 
"11", "12", "13", "14", "15", "16", "18", "19", "21", "3", "5", 
"6", "7", "8", "9", "pre"), class = "factor"), V3 = structure(c(19L, 
16L, 1L, 10L, 17L, 4L, 14L, 6L, 2L, 17L, 1L, 1L, 10L, 13L, 2L, 
9L, 14L, 7L, 18L, 2L, 18L, 6L, 3L, 9L, 15L, 12L, 5L, 15L, 8L, 
2L, 11L), .Label = c("0", "1", "10", "11", "12", "13", "14", 
"16", "18", "2", "20", "23", "3", "4", "5", "6", "8", "9", "post"
), class = "factor")), class = "data.frame", row.names = c(NA, 
-31L))
..Lifelength <-
structure(list(V1 = structure(c(9L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L), .Label = c("1", 
"2", "3", "4", "5", "6", "7", "8", "Category"), class = "factor"), 
    V2 = structure(c(74L, 14L, 19L, 23L, 27L, 29L, 31L, 32L, 
    35L, 35L, 35L, 36L, 36L, 36L, 38L, 41L, 42L, 42L, 42L, 43L, 
    44L, 44L, 45L, 46L, 47L, 49L, 51L, 52L, 52L, 53L, 53L, 53L, 
    55L, 55L, 55L, 56L, 57L, 57L, 58L, 59L, 59L, 60L, 60L, 62L, 
    62L, 64L, 66L, 69L, 2L, 2L, 3L, 4L, 4L, 6L, 8L, 8L, 8L, 9L, 
    9L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 
    15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 
    19L, 19L, 19L, 20L, 20L, 20L, 21L, 22L, 22L, 22L, 23L, 23L, 
    23L, 23L, 23L, 24L, 24L, 24L, 24L, 25L, 25L, 25L, 25L, 25L, 
    25L, 25L, 25L, 26L, 26L, 26L, 26L, 27L, 27L, 27L, 27L, 28L, 
    28L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 30L, 30L, 
    31L, 31L, 31L, 32L, 32L, 32L, 32L, 32L, 33L, 33L, 33L, 33L, 
    34L, 34L, 34L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 36L, 
    36L, 36L, 36L, 36L, 36L, 37L, 37L, 37L, 37L, 38L, 38L, 39L, 
    39L, 39L, 40L, 40L, 40L, 41L, 41L, 42L, 42L, 42L, 42L, 43L, 
    43L, 43L, 43L, 43L, 44L, 44L, 44L, 44L, 44L, 44L, 44L, 45L, 
    45L, 46L, 46L, 46L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 48L, 
    48L, 48L, 48L, 48L, 48L, 48L, 48L, 49L, 49L, 49L, 49L, 49L, 
    50L, 50L, 50L, 51L, 51L, 51L, 51L, 51L, 51L, 52L, 52L, 52L, 
    52L, 53L, 53L, 54L, 54L, 55L, 55L, 55L, 55L, 55L, 55L, 55L, 
    55L, 56L, 56L, 56L, 56L, 57L, 57L, 57L, 57L, 58L, 58L, 59L, 
    59L, 59L, 59L, 60L, 60L, 61L, 62L, 63L, 63L, 63L, 63L, 64L, 
    64L, 64L, 64L, 64L, 65L, 65L, 66L, 69L, 1L, 8L, 13L, 14L, 
    16L, 17L, 19L, 19L, 19L, 19L, 23L, 24L, 25L, 26L, 27L, 27L, 
    28L, 28L, 28L, 30L, 31L, 31L, 32L, 32L, 32L, 32L, 32L, 33L, 
    33L, 33L, 34L, 35L, 35L, 35L, 37L, 37L, 37L, 37L, 37L, 37L, 
    39L, 39L, 39L, 39L, 39L, 39L, 40L, 40L, 41L, 42L, 42L, 42L, 
    42L, 43L, 43L, 43L, 43L, 43L, 44L, 44L, 44L, 45L, 46L, 46L, 
    47L, 47L, 47L, 47L, 47L, 48L, 48L, 48L, 48L, 49L, 49L, 49L, 
    49L, 50L, 50L, 51L, 53L, 53L, 54L, 54L, 54L, 54L, 54L, 54L, 
    55L, 56L, 56L, 57L, 57L, 57L, 57L, 58L, 59L, 60L, 61L, 61L, 
    61L, 62L, 63L, 64L, 64L, 65L, 66L, 67L, 69L, 70L, 72L, 73L, 
    16L, 21L, 22L, 29L, 29L, 33L, 37L, 38L, 39L, 39L, 41L, 41L, 
    42L, 42L, 42L, 44L, 47L, 47L, 48L, 48L, 49L, 49L, 50L, 50L, 
    51L, 52L, 52L, 52L, 52L, 54L, 54L, 55L, 55L, 55L, 56L, 59L, 
    59L, 60L, 62L, 63L, 65L, 67L, 69L, 70L, 73L, 3L, 5L, 7L, 
    13L, 15L, 15L, 16L, 18L, 18L, 19L, 19L, 21L, 23L, 24L, 25L, 
    26L, 26L, 27L, 27L, 28L, 29L, 29L, 30L, 31L, 33L, 34L, 35L, 
    36L, 36L, 36L, 36L, 37L, 38L, 40L, 40L, 41L, 42L, 43L, 43L, 
    43L, 44L, 44L, 45L, 46L, 46L, 46L, 46L, 46L, 46L, 47L, 48L, 
    50L, 51L, 51L, 51L, 53L, 53L, 54L, 54L, 55L, 55L, 56L, 57L, 
    58L, 58L, 59L, 60L, 60L, 60L, 60L, 60L, 61L, 63L, 64L, 64L, 
    66L, 66L, 69L, 69L, 69L, 70L, 70L, 33L, 33L, 34L, 34L, 39L, 
    40L, 42L, 43L, 43L, 44L, 45L, 45L, 46L, 46L, 46L, 47L, 48L, 
    49L, 50L, 51L, 51L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 57L, 
    58L, 58L, 60L, 61L, 61L, 61L, 63L, 63L, 63L, 64L, 65L, 65L, 
    66L, 67L, 7L, 16L, 17L, 21L, 24L, 24L, 25L, 26L, 28L, 32L, 
    35L, 39L, 39L, 40L, 40L, 41L, 41L, 41L, 41L, 42L, 42L, 43L, 
    43L, 45L, 45L, 46L, 47L, 47L, 48L, 48L, 48L, 48L, 49L, 49L, 
    49L, 49L, 50L, 51L, 51L, 51L, 51L, 52L, 52L, 53L, 54L, 54L, 
    55L, 55L, 55L, 56L, 59L, 59L, 59L, 60L, 60L, 60L, 61L, 62L, 
    62L, 65L, 67L, 70L, 71L, 19L, 23L, 23L, 26L, 27L, 28L, 28L, 
    34L, 35L, 35L, 37L, 38L, 39L, 39L, 39L, 40L, 40L, 41L, 41L, 
    41L, 43L, 44L, 44L, 44L, 45L, 45L, 45L, 45L, 46L, 47L, 48L, 
    48L, 49L, 49L, 49L, 49L, 50L, 51L, 52L, 53L, 53L, 53L, 53L, 
    54L, 54L, 55L, 55L, 56L, 56L, 56L, 56L, 56L, 57L, 57L, 57L, 
    58L, 59L, 59L, 59L, 59L, 61L, 61L, 62L, 62L, 62L, 63L, 63L, 
    63L, 64L, 65L, 65L, 68L, 69L, 70L, 71L, 72L), .Label = c("115", 
    "21", "22", "24", "26", "27", "28", "29", "30", "31", "32", 
    "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", 
    "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", 
    "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", 
    "63", "64", "65", "66", "67", "68", "69", "70", "71", "72", 
    "73", "74", "75", "76", "77", "78", "79", "80", "81", "82", 
    "83", "84", "85", "86", "87", "88", "89", "90", "91", "92", 
    "93", "96", "Lifelength"), class = "factor")), class = "data.frame", row.names = c(NA, 
-691L))
..olympic <-
structure(list(V1 = structure(c(21L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
20L), .Label = c("1900", "1904", "1908", "1912", "1920", "1924", 
"1928", "1932", "1936", "1948", "1952", "1956", "1960", "1964", 
"1968", "1972", "1976", "1980", "1984", "1988", "Year"), class = "factor"), 
    V2 = structure(c(11L, 10L, 12L, 10L, 10L, 10L, 9L, 10L, 6L, 
    6L, 6L, 7L, 8L, 4L, 1L, 14L, 3L, 2L, 5L, 15L, 13L), .Label = c("10", 
    "10.06", "10.14", "10.2", "10.25", "10.3", "10.4", "10.5", 
    "10.6", "10.8", "100m", "11", "9.92", "9.95", "9.99"), class = "factor"), 
    V3 = structure(c(11L, 18L, 14L, 19L, 15L, 17L, 14L, 16L, 
    13L, 10L, 12L, 10L, 9L, 8L, 7L, 3L, 4L, 6L, 5L, 2L, 1L), .Label = c("19.75", 
    "19.8", "19.83", "20", "20.19", "20.23", "20.3", "20.5", 
    "20.6", "20.7", "200m", "21.1", "21.2", "21.6", "21.7", "21.8", 
    "22", "22.2", "22.4"), class = "factor"), V4 = structure(c(1L, 
    18L, 17L, 20L, 16L, 19L, 14L, 15L, 11L, 12L, 11L, 10L, 13L, 
    8L, 9L, 2L, 7L, 4L, 6L, 5L, 3L), .Label = c("400m", "43.8", 
    "43.87", "44.26", "44.27", "44.6", "44.66", "44.9", "45.1", 
    "45.9", "46.2", "46.5", "46.7", "47.6", "47.8", "48.2", "49.2", 
    "49.4", "49.6", "50"), class = "factor"), V5 = structure(c(20L, 
    19L, 18L, 15L, 13L, 17L, 14L, 12L, 11L, 16L, 10L, 10L, 9L, 
    8L, 5L, 4L, 7L, 3L, 6L, 1L, 2L), .Label = c("103", "103.45", 
    "103.5", "104.3", "105.1", "105.4", "105.9", "106.3", "107.7", 
    "109.2", "109.8", "111.8", "111.9", "112.4", "112.8", "112.9", 
    "113.4", "116", "121.4", "800m"), class = "factor"), V6 = structure(c(1L, 
    20L, 19L, 18L, 16L, 17L, 15L, 14L, 13L, 12L, 11L, 11L, 10L, 
    4L, 7L, 3L, 6L, 9L, 8L, 2L, 5L), .Label = c("1500m", "212.5", 
    "214.9", "215.6", "215.96", "216.3", "218.1", "218.4", "219.2", 
    "221.2", "225.2", "227.8", "231.2", "233.2", "233.6", "236.8", 
    "241.8", "243.4", "245.4", "246"), class = "factor")), class = "data.frame", row.names = c(NA, 
-21L))
..poison <-
structure(list(V1 = structure(c(35L, 12L, 21L, 22L, 19L, 32L, 
3L, 33L, 30L, 19L, 21L, 27L, 31L, 21L, 29L, 28L, 26L, 15L, 10L, 
18L, 7L, 34L, 25L, 23L, 4L, 20L, 14L, 12L, 18L, 24L, 2L, 29L, 
17L, 6L, 5L, 1L, 7L, 11L, 16L, 17L, 10L, 7L, 9L, 8L, 6L, 11L, 
15L, 12L, 13L), .Label = c("1.8", "10.2", "11", "12.4", "2.1", 
"2.2", "2.3", "2.4", "2.5", "2.9", "3", "3.1", "3.3", "3.5", 
"3.6", "3.7", "3.8", "4", "4.3", "4.4", "4.5", "4.6", "4.9", 
"5.6", "6.1", "6.2", "6.3", "6.6", "7.1", "7.2", "7.6", "8.2", 
"8.8", "9.2", "Survtime"), class = "factor"), V2 = structure(c(5L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L
), .Label = c("1", "2", "3", "4", "Treatment"), class = "factor"), 
    V3 = structure(c(4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("1", "2", 
    "3", "Poison"), class = "factor")), class = "data.frame", row.names = c(NA, 
-49L))
..skulls <-
structure(list(V1 = structure(c(27L, 10L, 4L, 10L, 1L, 15L, 17L, 
18L, 4L, 10L, 13L, 8L, 13L, 5L, 11L, 20L, 10L, 14L, 11L, 18L, 
11L, 5L, 14L, 13L, 7L, 9L, 17L, 7L, 6L, 10L, 3L, 3L, 12L, 17L, 
26L, 5L, 14L, 11L, 12L, 10L, 12L, 12L, 10L, 10L, 17L, 9L, 10L, 
17L, 2L, 9L, 13L, 16L, 5L, 14L, 8L, 13L, 10L, 11L, 9L, 14L, 9L, 
16L, 8L, 11L, 9L, 13L, 19L, 17L, 15L, 15L, 5L, 16L, 16L, 15L, 
16L, 8L, 14L, 8L, 13L, 17L, 15L, 11L, 12L, 17L, 9L, 15L, 13L, 
15L, 12L, 17L, 17L, 16L, 20L, 20L, 14L, 12L, 10L, 19L, 18L, 19L, 
17L, 11L, 13L, 14L, 12L, 15L, 13L, 10L, 8L, 15L, 10L, 18L, 23L, 
20L, 9L, 12L, 17L, 10L, 15L, 11L, 14L, 16L, 15L, 7L, 9L, 17L, 
5L, 15L, 5L, 11L, 18L, 22L, 20L, 14L, 16L, 21L, 18L, 17L, 16L, 
12L, 24L, 17L, 10L, 22L, 13L, 11L, 16L, 8L, 19L, 25L, 15L), .Label = c("119", 
"123", "124", "125", "126", "127", "128", "129", "130", "131", 
"132", "133", "134", "135", "136", "137", "138", "139", "140", 
"141", "142", "143", "144", "145", "147", "148", "MB"), class = "factor"), 
    V2 = structure(c(25L, 18L, 11L, 12L, 12L, 23L, 17L, 10L, 
    16L, 14L, 14L, 18L, 2L, 9L, 16L, 20L, 14L, 17L, 13L, 16L, 
    11L, 13L, 15L, 4L, 14L, 10L, 15L, 12L, 9L, 16L, 18L, 18L, 
    14L, 14L, 9L, 4L, 16L, 24L, 10L, 14L, 5L, 16L, 19L, 16L, 
    14L, 16L, 8L, 9L, 11L, 9L, 10L, 16L, 11L, 16L, 6L, 19L, 14L, 
    10L, 12L, 12L, 8L, 21L, 13L, 18L, 14L, 14L, 13L, 18L, 24L, 
    11L, 16L, 9L, 19L, 6L, 13L, 22L, 18L, 15L, 5L, 14L, 15L, 
    10L, 11L, 17L, 7L, 13L, 3L, 17L, 11L, 13L, 13L, 14L, 8L, 
    10L, 11L, 1L, 15L, 17L, 10L, 14L, 20L, 13L, 14L, 15L, 16L, 
    10L, 17L, 21L, 15L, 8L, 5L, 10L, 4L, 11L, 11L, 8L, 6L, 22L, 
    18L, 16L, 10L, 3L, 11L, 6L, 14L, 7L, 18L, 18L, 6L, 12L, 15L, 
    1L, 16L, 15L, 14L, 15L, 14L, 5L, 15L, 5L, 9L, 16L, 9L, 6L, 
    4L, 7L, 5L, 8L, 15L, 9L, 13L), .Label = c("120", "121", "123", 
    "124", "125", "126", "127", "128", "129", "130", "131", "132", 
    "133", "134", "135", "136", "137", "138", "139", "140", "141", 
    "142", "143", "145", "BH"), class = "factor"), V3 = structure(c(28L, 
    17L, 20L, 27L, 24L, 1L, 17L, 9L, 21L, 3L, 27L, 23L, 23L, 
    10L, 1L, 1L, 25L, 4L, 21L, 24L, 2L, 3L, 4L, 21L, 4L, 5L, 
    1L, 21L, 7L, 11L, 2L, 2L, 25L, 26L, 5L, 23L, 26L, 1L, 3L, 
    24L, 22L, 4L, 26L, 27L, 26L, 5L, 26L, 8L, 2L, 6L, 21L, 7L, 
    1L, 25L, 19L, 2L, 18L, 5L, 21L, 26L, 2L, 24L, 21L, 15L, 7L, 
    24L, 26L, 23L, 27L, 20L, 23L, 1L, 25L, 2L, 18L, 5L, 3L, 20L, 
    18L, 24L, 22L, 19L, 1L, 22L, 27L, 19L, 23L, 2L, 24L, 1L, 
    19L, 8L, 23L, 15L, 27L, 19L, 18L, 22L, 18L, 18L, 1L, 18L, 
    25L, 27L, 23L, 27L, 21L, 27L, 23L, 21L, 16L, 22L, 14L, 25L, 
    26L, 20L, 25L, 23L, 22L, 20L, 1L, 19L, 23L, 19L, 20L, 14L, 
    2L, 25L, 20L, 27L, 20L, 23L, 2L, 23L, 21L, 24L, 23L, 27L, 
    24L, 20L, 17L, 20L, 25L, 16L, 19L, 25L, 13L, 12L, 4L, 15L, 
    25L), .Label = c("100", "101", "102", "103", "104", "105", 
    "106", "107", "108", "109", "114", "81", "85", "86", "87", 
    "88", "89", "90", "91", "92", "93", "94", "95", "96", "97", 
    "98", "99", "BL"), class = "factor"), V4 = structure(c(17L, 
    6L, 5L, 7L, 1L, 11L, 13L, 5L, 5L, 8L, 8L, 7L, 10L, 8L, 7L, 
    8L, 11L, 7L, 10L, 7L, 6L, 8L, 4L, 10L, 7L, 6L, 12L, 10L, 
    5L, 11L, 3L, 5L, 5L, 2L, 8L, 2L, 9L, 11L, 5L, 7L, 3L, 10L, 
    8L, 13L, 6L, 10L, 2L, 10L, 8L, 4L, 11L, 6L, 5L, 9L, 7L, 6L, 
    10L, 7L, 9L, 11L, 8L, 9L, 4L, 5L, 7L, 2L, 7L, 4L, 12L, 3L, 
    13L, 10L, 7L, 7L, 6L, 4L, 12L, 7L, 16L, 8L, 10L, 9L, 7L, 
    8L, 2L, 6L, 9L, 11L, 6L, 12L, 3L, 11L, 10L, 6L, 8L, 3L, 7L, 
    16L, 5L, 8L, 9L, 10L, 11L, 7L, 9L, 12L, 9L, 12L, 4L, 11L, 
    5L, 10L, 7L, 10L, 10L, 8L, 11L, 10L, 12L, 9L, 8L, 7L, 6L, 
    14L, 9L, 4L, 9L, 15L, 2L, 12L, 11L, 8L, 11L, 13L, 10L, 9L, 
    4L, 8L, 11L, 7L, 4L, 3L, 1L, 11L, 12L, 9L, 14L, 9L, 5L, 5L, 
    8L), .Label = c("44", "45", "46", "47", "48", "49", "50", 
    "51", "52", "53", "54", "55", "56", "57", "58", "60", "NH"
    ), class = "factor"), V5 = structure(c(6L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("-1850", 
    "-200", "-3300", "-4000", "150", "Year"), class = "factor")), class = "data.frame", row.names = c(NA, 
-151L))
..splett2 <-
structure(list(V1 = structure(c(52L, 17L, 6L, 38L, 44L, 4L, 15L, 
11L, 20L, 7L, 30L, 2L, 9L, 14L, 15L, 30L, 32L, 29L, 24L, 15L, 
23L, 3L, 13L, 5L, 22L, 27L, 10L, 31L, 25L, 9L, 18L, 25L, 12L, 
43L, 27L, 27L, 48L, 21L, 25L, 18L, 31L, 27L, 41L, 21L, 27L, 27L, 
35L, 21L, 49L, 15L, 43L, 51L, 49L, 39L, 40L, 46L, 38L, 38L, 34L, 
48L, 38L, 41L, 40L, 45L, 49L, 34L, 34L, 50L, 47L, 28L, 26L, 25L, 
32L, 43L, 34L, 19L, 1L, 8L, 8L, 23L, 36L, 19L, 37L, 42L, 23L, 
19L, 16L, 16L, 23L, 5L, 12L, 19L, 16L, 36L, 16L, 5L, 19L, 19L, 
33L, 33L), .Label = c("64.2", "64.5", "65", "65.2", "65.4", "65.5", 
"65.8", "65.9", "66", "66.2", "66.3", "66.5", "66.6", "66.8", 
"67", "67.1", "67.4", "67.5", "67.6", "67.9", "68", "68.1", "68.2", 
"68.3", "68.5", "68.8", "69", "69.5", "69.7", "69.9", "70", "70.1", 
"70.5", "70.9", "71", "71.1", "71.6", "72", "72.3", "72.4", "72.5", 
"72.8", "73", "73.6", "74", "74.1", "74.2", "74.5", "75", "76.6", 
"78.9", "Energy"), class = "factor"), V2 = structure(c(5L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L), .Label = c("1", "2", "3", "4", "Machine"), class = "factor")), class = "data.frame", row.names = c(NA, 
-100L))
..stars1 <-
structure(list(V1 = structure(c(16L, 1L, 2L, 3L, 4L, 5L, 5L, 
6L, 7L, 7L, 8L, 9L, 10L, 10L, 10L, 10L, 11L, 12L, 12L, 13L, 14L, 
15L, 15L, 15L, 15L), .Label = c("0.032", "0.034", "0.214", "0.263", 
"0.275", "0.45", "0.5", "0.63", "0.8", "0.9", "1", "1.1", "1.4", 
"1.7", "2", "Distance"), class = "factor"), V2 = structure(c(21L, 
9L, 12L, 1L, 6L, 2L, 4L, 10L, 12L, 11L, 3L, 13L, 5L, 16L, 8L, 
15L, 19L, 14L, 15L, 15L, 20L, 15L, 18L, 17L, 7L), .Label = c("-130", 
"-185", "-200", "-220", "-30", "-70", "1090", "150", "170", "200", 
"270", "290", "300", "450", "500", "650", "800", "850", "920", 
"960", "Velocity"), class = "factor")), class = "data.frame", row.names = c(NA, 
-25L))
..stars2 <-
structure(list(V1 = structure(c(22L, 1L, 16L, 19L, 20L, 21L, 
6L, 8L, 12L, 2L, 3L, 4L, 5L, 15L, 14L, 11L, 18L, 10L, 17L, 13L, 
7L, 9L), .Label = c("1.6", "1.8", "10.2", "12", "12.5", "13.4", 
"16.5", "21.1", "22.2", "27.6", "34", "35.1", "37.6", "41.2", 
"43", "6.8", "69.9", "75.3", "8.3", "8.6", "9.4", "Distance"), class = "factor"), 
    V2 = structure(c(22L, 20L, 10L, 13L, 14L, 15L, 19L, 2L, 6L, 
    1L, 16L, 17L, 18L, 9L, 8L, 5L, 12L, 4L, 11L, 7L, 21L, 3L), .Label = c("1000", 
    "11800", "12400", "15400", "19000", "19600", "21000", "23000", 
    "24000", "3810", "39000", "42000", "4630", "4820", "5230", 
    "5700", "6700", "7000", "7500", "890", "9200", "Velocity"
    ), class = "factor")), class = "data.frame", row.names = c(NA, 
-22L))
..trout <-
structure(list(V1 = structure(c(5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L), .Label = c("0", "10", "15", "5", "Sulfamerazine"), class = "factor"), 
    V2 = structure(c(24L, 9L, 14L, 6L, 17L, 10L, 14L, 18L, 13L, 
    7L, 10L, 23L, 17L, 2L, 22L, 4L, 5L, 11L, 8L, 18L, 3L, 2L, 
    16L, 3L, 19L, 4L, 21L, 20L, 16L, 14L, 15L, 22L, 22L, 12L, 
    14L, 22L, 1L, 19L, 18L, 22L, 12L), .Label = c("10.2", "10.4", 
    "10.6", "10.7", "11.9", "5.5", "5.8", "6.4", "6.7", "7", 
    "7.1", "7.2", "7.4", "7.8", "8", "8.1", "8.4", "8.6", "8.7", 
    "8.8", "9.1", "9.3", "9.9", "Hemoglobin"), class = "factor")), class = "data.frame", row.names = c(NA, 
-41L))
..Waist <-
structure(list(V1 = structure(c(89L, 38L, 32L, 57L, 65L, 37L, 
30L, 56L, 61L, 28L, 34L, 31L, 39L, 33L, 49L, 45L, 29L, 42L, 36L, 
35L, 41L, 44L, 56L, 53L, 75L, 58L, 80L, 72L, 69L, 59L, 62L, 74L, 
78L, 76L, 5L, 83L, 79L, 7L, 54L, 49L, 62L, 43L, 55L, 71L, 60L, 
14L, 82L, 83L, 51L, 50L, 77L, 64L, 67L, 40L, 47L, 48L, 73L, 70L, 
68L, 63L, 46L, 66L, 52L, 17L, 25L, 26L, 84L, 11L, 10L, 13L, 13L, 
3L, 85L, 1L, 16L, 1L, 7L, 9L, 12L, 19L, 8L, 21L, 21L, 23L, 18L, 
9L, 22L, 18L, 27L, 19L, 86L, 11L, 87L, 83L, 85L, 10L, 12L, 88L, 
79L, 6L, 12L, 20L, 24L, 3L, 2L, 81L, 4L, 15L, 18L, 55L), .Label = c("100", 
"100.1", "101", "101.8", "102", "102.5", "103", "103.5", "104", 
"105", "105.5", "106", "107", "107.1", "107.9", "108", "108.3", 
"108.5", "109", "109.1", "110", "111", "112", "115", "119.6", 
"119.9", "121", "63.5", "68.85", "71.85", "71.9", "72.6", "73.1", 
"73.2", "73.8", "74.15", "74.65", "74.75", "75", "75.5", "75.9", 
"75.95", "76", "76.85", "77", "77.6", "78.4", "78.6", "79", "79.3", 
"79.7", "79.8", "79.9", "80", "80.5", "80.9", "81.8", "82", "82.5", 
"83", "83.4", "83.5", "83.7", "83.8", "83.95", "84.9", "85.2", 
"85.5", "86", "86.3", "86.5", "86.6", "87.8", "88.1", "89.2", 
"89.4", "89.8", "90.8", "91", "92", "93.3", "94.3", "94.5", "96.5", 
"97", "97.5", "98", "99", "Waist"), class = "factor"), V2 = structure(c(100L, 
44L, 45L, 63L, 64L, 51L, 39L, 49L, 54L, 5L, 53L, 48L, 67L, 58L, 
62L, 52L, 72L, 66L, 55L, 65L, 50L, 57L, 59L, 56L, 75L, 68L, 79L, 
89L, 85L, 77L, 81L, 94L, 86L, 90L, 14L, 9L, 3L, 15L, 83L, 71L, 
82L, 69L, 70L, 20L, 97L, 8L, 3L, 10L, 78L, 88L, 6L, 96L, 17L, 
61L, 60L, 74L, 93L, 27L, 80L, 84L, 73L, 99L, 47L, 10L, 95L, 2L, 
21L, 9L, 98L, 31L, 92L, 26L, 1L, 10L, 40L, 20L, 4L, 14L, 7L, 
36L, 16L, 13L, 25L, 28L, 33L, 34L, 9L, 29L, 43L, 19L, 30L, 24L, 
32L, 87L, 19L, 12L, 42L, 18L, 22L, 37L, 23L, 41L, 46L, 35L, 11L, 
76L, 17L, 38L, 38L, 91L), .Label = c("100", "106", "107", "109", 
"11.44", "111", "112", "118", "121", "123", "124", "125", "126", 
"127", "129", "132", "133", "134", "137", "140", "144", "150", 
"151", "152", "153", "154", "155", "158", "159", "165", "166", 
"181", "183", "184", "188", "192", "198", "208", "21.68", "217", 
"229", "241", "245", "25.72", "25.89", "253", "27.96", "28.32", 
"29.08", "29.31", "29.84", "30.96", "32.22", "32.98", "33.41", 
"35.43", "36.6", "38.21", "40.25", "41.71", "41.9", "42.48", 
"42.6", "42.8", "43.35", "43.78", "43.86", "45.84", "50.5", "50.88", 
"55.48", "55.78", "57.05", "58.16", "60.09", "62.2", "64.75", 
"65.92", "70.4", "70.77", "72.56", "73.13", "74.02", "75.08", 
"78.89", "78.94", "80.95", "81.29", "83.45", "83.55", "84.3", 
"87.99", "88.85", "89.31", "90.41", "90.73", "96.54", "97.13", 
"99.73", "AT"), class = "factor")), class = "data.frame", row.names = c(NA, 
-110L))
..Worldpop <-
structure(list(V1 = structure(c(21L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 
20L), .Label = c("1981", "1982", "1983", "1984", "1985", "1986", 
"1987", "1988", "1989", "1990", "1991", "1992", "1993", "1994", 
"1995", "1996", "1997", "1998", "1999", "2000", "Year"), class = "factor"), 
    V2 = structure(c(21L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
    10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L), .Label = c("4.533", 
    "4.613", "4.694", "4.774", "4.855", "4.938", "5.024", "5.11", 
    "5.196", "5.284", "5.367", "5.45", "5.531", "5.611", "5.691", 
    "5.769", "5.847", "5.925", "6.003", "6.08", "Pop.billion"
    ), class = "factor")), class = "data.frame", row.names = c(NA, 
-21L))
..Worldrecord <-
structure(list(V1 = structure(c(11L, 1L, 5L, 8L, 10L, 2L, 4L, 
6L, 7L, 9L, 3L), .Label = c("100", "1000", "10000", "1500", "200", 
"2000", "3000", "400", "5000", "800", "Distance"), class = "factor"), 
    V2 = structure(c(11L, 10L, 4L, 7L, 1L, 2L, 5L, 6L, 8L, 9L, 
    3L), .Label = c("100.91", "131.96", "1577.53", "19.19", "206", 
    "284.79", "43.03", "440.67", "757.35", "9.58", "MenRecord"
    ), class = "factor"), V3 = structure(c(11L, 1L, 5L, 8L, 2L, 
    3L, 6L, 7L, 9L, 10L, 4L), .Label = c("10.49", "113.28", "148.98", 
    "1757.45", "21.34", "230.07", "323.75", "47.6", "486.11", 
    "851.15", "WomenRecord"), class = "factor")), class = "data.frame", row.names = c(NA, 
-11L))
..Wright <-
structure(list(V1 = structure(c(60L, 1L, 12L, 33L, 58L, 3L, 7L, 
11L, 16L, 20L, 27L, 31L, 30L, 22L, 20L, 1L, 44L, 3L, 9L, 15L, 
20L, 24L, 25L, 26L, 26L, 24L, 23L, 21L, 20L, 1L, 57L, 5L, 13L, 
20L, 23L, 25L, 26L, 26L, 25L, 25L, 25L, 25L, 25L, 57L, 3L, 7L, 
10L, 15L, 20L, 25L, 30L, 36L, 43L, 51L, 52L, 41L, 28L, 53L, 58L, 
4L, 8L, 11L, 17L, 21L, 26L, 32L, 41L, 48L, 49L, 34L, 26L, 44L, 
58L, 3L, 7L, 11L, 15L, 20L, 25L, 29L, 38L, 43L, 45L, 31L, 23L, 
58L, 9L, 18L, 24L, 31L, 47L, 55L, 56L, 54L, 45L, 40L, 39L, 37L, 
35L, 58L, 9L, 16L, 22L, 32L, 43L, 49L, 50L, 47L, 41L, 38L, 36L, 
35L, 32L, 58L, 7L, 15L, 20L, 32L, 40L, 45L, 46L, 42L, 38L, 35L, 
34L, 34L, 31L, 57L, 10L, 19L, 26L, 29L, 29L, 31L, 32L, 35L, 38L, 
35L, 32L, 32L, 31L, 57L, 8L, 18L, 25L, 30L, 30L, 31L, 35L, 36L, 
35L, 32L, 31L, 31L, 30L, 53L, 5L, 15L, 25L, 32L, 38L, 40L, 39L, 
38L, 35L, 32L, 31L, 31L, 29L, 58L, 7L, 15L, 20L, 22L, 23L, 25L, 
27L, 28L, 29L, 30L, 23L, 33L, 58L, 4L, 8L, 11L, 17L, 22L, 29L, 
34L, 43L, 50L, 47L, 31L, 23L, 33L, 53L, 2L, 6L, 11L, 15L, 21L, 
26L, 30L, 41L, 47L, 42L, 27L, 22L, 33L, 53L, 59L, 5L, 9L, 14L, 
19L, 24L, 28L, 38L, 43L, 39L, 25L, 22L), .Label = c("0", "10", 
"11", "12", "13", "14", "15", "16", "17", "18", "19", "2", "20", 
"21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", 
"32", "33", "34", "35", "36", "37", "38", "39", "4", "40", "41", 
"42", "43", "44", "45", "46", "47", "48", "49", "5", "50", "51", 
"52", "54", "55", "56", "57", "58", "6", "60", "61", "63", "7", 
"8", "9", "Pressure"), class = "factor"), V2 = structure(c(15L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 6L, 13L, 14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 12L, 1L, 6L, 13L, 
14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 6L, 13L, 
14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 6L, 13L, 
14L, 2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L), .Label = c("0", 
"10", "12.5", "15", "17.5", "2.5", "20", "25", "30", "35", "40", 
"45", "5", "7.5", "Angle"), class = "factor"), V3 = structure(c(17L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
14L, 14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 
16L, 16L, 16L, 16L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L), .Label = c("1", "10", "11", "12", "13", 
"15", "16", "17", "2", "3", "4", "5", "6", "7", "8", "9", "Wing"
), class = "factor")), class = "data.frame", row.names = c(NA, 
-223L))
`./airspeed.txt` <-
structure(list(Posmaxspeed = c(-0.024, -0.023, 0.001, 0.008, 
0.029, 0.023, 0.033, 0.028, 0.045, 0.057, 0.074, 0.08, 0.037, 
0.079, 0.079, 0.095, 0.101, 0.111), Reynolds = c(4.8, 4.9, 5, 
5.1, 5.2, 5.3, 4.8, 4.9, 5, 5.1, 5.2, 5.3, 4.8, 4.9, 5, 5.1, 
5.2, 5.3), Ribht = c(0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.015, 
0.015, 0.015, 0.015, 0.015, 0.015, 0.02, 0.02, 0.02, 0.02, 0.02, 
0.02)), class = "data.frame", row.names = c(NA, -18L))
`./appletree.txt` <-
structure(list(Treatment = c(1L, 2L, 3L, 4L, 5L, 0L, 1L, 2L, 
3L, 4L, 5L, 0L, 1L, 2L, 3L, 4L, 5L, 0L, 1L, 2L, 3L, 4L, 5L, 0L
), Block = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L), Volume = c(8.2, 
8.2, 6.8, 5.7, 6.1, 7.6, 9.4, 6, 7, 5.5, 7, 10.1, 7.7, 9.1, 9.7, 
10.2, 8.7, 9, 8.5, 10.1, 9.9, 10.3, 8.1, 10.5), Weight = c(287L, 
271L, 234L, 189L, 210L, 222L, 290L, 209L, 210L, 205L, 276L, 301L, 
254L, 243L, 286L, 312L, 279L, 238L, 307L, 348L, 371L, 375L, 344L, 
357L)), class = "data.frame", row.names = c(NA, -24L))
`./Birthwt.txt` <-
structure(list(LOW = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), AGE = c(19L, 33L, 20L, 21L, 18L, 21L, 22L, 17L, 
29L, 26L, 19L, 19L, 22L, 30L, 18L, 18L, 15L, 25L, 20L, 28L, 32L, 
31L, 36L, 28L, 25L, 28L, 17L, 29L, 26L, 17L, 17L, 24L, 35L, 25L, 
25L, 29L, 19L, 27L, 31L, 33L, 21L, 19L, 23L, 21L, 18L, 18L, 32L, 
19L, 24L, 22L, 22L, 23L, 22L, 30L, 19L, 16L, 21L, 30L, 20L, 17L, 
17L, 23L, 24L, 28L, 26L, 20L, 24L, 28L, 20L, 22L, 22L, 31L, 23L, 
16L, 16L, 18L, 25L, 32L, 20L, 23L, 22L, 32L, 30L, 20L, 23L, 17L, 
19L, 23L, 36L, 22L, 24L, 21L, 19L, 25L, 16L, 29L, 29L, 19L, 19L, 
30L, 24L, 19L, 24L, 23L, 20L, 25L, 30L, 22L, 18L, 16L, 32L, 18L, 
29L, 33L, 20L, 28L, 14L, 28L, 25L, 16L, 20L, 26L, 21L, 22L, 25L, 
31L, 35L, 19L, 24L, 45L, 28L, 29L, 34L, 25L, 25L, 27L, 23L, 24L, 
24L, 21L, 32L, 19L, 25L, 16L, 25L, 20L, 21L, 24L, 21L, 20L, 25L, 
19L, 19L, 26L, 24L, 17L, 20L, 22L, 27L, 20L, 17L, 25L, 20L, 18L, 
18L, 20L, 21L, 26L, 31L, 15L, 23L, 20L, 24L, 15L, 23L, 30L, 22L, 
17L, 23L, 17L, 26L, 20L, 26L, 14L, 28L, 14L, 23L, 17L, 21L), 
    LWT = c(182L, 155L, 105L, 108L, 107L, 124L, 118L, 103L, 123L, 
    113L, 95L, 150L, 95L, 107L, 100L, 100L, 98L, 118L, 120L, 
    120L, 121L, 100L, 202L, 120L, 120L, 167L, 122L, 150L, 168L, 
    113L, 113L, 90L, 121L, 155L, 125L, 140L, 138L, 124L, 215L, 
    109L, 185L, 189L, 130L, 160L, 90L, 90L, 132L, 132L, 115L, 
    85L, 120L, 128L, 130L, 95L, 115L, 110L, 110L, 153L, 103L, 
    119L, 119L, 119L, 110L, 140L, 133L, 169L, 115L, 250L, 141L, 
    158L, 112L, 150L, 115L, 112L, 135L, 229L, 140L, 134L, 121L, 
    190L, 131L, 170L, 110L, 127L, 123L, 120L, 105L, 130L, 175L, 
    125L, 133L, 134L, 235L, 95L, 135L, 135L, 154L, 147L, 147L, 
    137L, 110L, 184L, 110L, 110L, 120L, 241L, 112L, 169L, 120L, 
    170L, 186L, 120L, 130L, 117L, 170L, 134L, 135L, 130L, 120L, 
    95L, 158L, 160L, 115L, 129L, 130L, 120L, 170L, 120L, 116L, 
    123L, 120L, 130L, 187L, 105L, 85L, 150L, 97L, 128L, 132L, 
    165L, 105L, 91L, 115L, 130L, 92L, 150L, 200L, 155L, 103L, 
    125L, 89L, 102L, 112L, 117L, 138L, 130L, 120L, 130L, 130L, 
    80L, 110L, 105L, 109L, 148L, 110L, 121L, 100L, 96L, 102L, 
    110L, 187L, 122L, 105L, 115L, 120L, 142L, 130L, 120L, 110L, 
    120L, 154L, 105L, 190L, 101L, 95L, 100L, 94L, 142L, 130L), 
    RACE = c(3L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 
    1L, 1L, 2L, 2L, 3L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 
    2L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 
    3L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 
    1L, 3L, 2L, 3L, 2L, 2L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
    2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    1L, 2L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 
    3L, 1L, 1L, 1L, 1L, 3L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 3L, 
    2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 3L, 2L, 3L, 1L, 2L, 1L, 
    1L, 1L, 3L, 2L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 
    2L, 2L, 3L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 3L, 2L), SMOKE = c(0L, 
    0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 
    0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 
    1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 
    0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 
    0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 
    0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 
    0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 
    0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L), PTL = c(0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    2L, 1L, 0L, 0L, 2L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 3L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 2L, 0L, 0L, 1L, 
    0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L), HT = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    1L), UI = c(1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 
    0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 
    0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), FTV = c(0L, 
    3L, 1L, 2L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 
    0L, 3L, 0L, 1L, 2L, 3L, 1L, 0L, 2L, 0L, 0L, 2L, 0L, 1L, 1L, 
    1L, 1L, 1L, 0L, 2L, 2L, 0L, 2L, 1L, 2L, 2L, 1L, 0L, 0L, 0L, 
    4L, 0L, 2L, 0L, 1L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    2L, 0L, 0L, 0L, 1L, 2L, 6L, 1L, 2L, 0L, 2L, 1L, 0L, 0L, 0L, 
    1L, 4L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 
    1L, 0L, 2L, 4L, 2L, 1L, 2L, 1L, 0L, 1L, 0L, 0L, 2L, 1L, 1L, 
    0L, 1L, 0L, 2L, 2L, 1L, 0L, 1L, 1L, 0L, 2L, 0L, 0L, 0L, 0L, 
    1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 2L, 2L, 0L, 0L, 0L, 1L, 
    2L, 0L, 0L, 0L, 0L, 3L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    4L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 3L, 0L, 2L, 1L, 
    3L, 0L, 0L, 2L, 2L, 0L, 0L, 3L), BWT = c(2523L, 2551L, 2557L, 
    2594L, 2600L, 2622L, 2637L, 2637L, 2663L, 2665L, 2722L, 2733L, 
    2750L, 2750L, 2769L, 2769L, 2778L, 2782L, 2807L, 2821L, 2835L, 
    2835L, 2836L, 2863L, 2877L, 2877L, 2906L, 2920L, 2920L, 2920L, 
    2920L, 2948L, 2948L, 2977L, 2977L, 2977L, 2977L, 2992L, 3005L, 
    3033L, 3042L, 3062L, 3062L, 3062L, 3076L, 3076L, 3080L, 3090L, 
    3090L, 3090L, 3100L, 3104L, 3132L, 3147L, 3175L, 3175L, 3203L, 
    3203L, 3203L, 3225L, 3225L, 3232L, 3232L, 3234L, 3260L, 3274L, 
    3274L, 3303L, 3317L, 3317L, 3317L, 3321L, 3331L, 3374L, 3374L, 
    3402L, 3416L, 3430L, 3444L, 3459L, 3460L, 3473L, 3475L, 3487L, 
    3544L, 3572L, 3572L, 3586L, 3600L, 3614L, 3614L, 3629L, 3629L, 
    3637L, 3643L, 3651L, 3651L, 3651L, 3651L, 3699L, 3728L, 3756L, 
    3770L, 3770L, 3770L, 3790L, 3799L, 3827L, 3856L, 3860L, 3860L, 
    3884L, 3884L, 3912L, 3940L, 3941L, 3941L, 3969L, 3983L, 3997L, 
    3997L, 4054L, 4054L, 4111L, 4153L, 4167L, 4174L, 4238L, 4593L, 
    4990L, 709L, 1021L, 1135L, 1330L, 1474L, 1588L, 1588L, 1701L, 
    1729L, 1790L, 1818L, 1885L, 1893L, 1899L, 1928L, 1928L, 1928L, 
    1936L, 1970L, 2055L, 2055L, 2082L, 2084L, 2084L, 2100L, 2125L, 
    2126L, 2187L, 2187L, 2211L, 2225L, 2240L, 2240L, 2282L, 2296L, 
    2296L, 2301L, 2325L, 2353L, 2353L, 2367L, 2381L, 2381L, 2381L, 
    2395L, 2410L, 2410L, 2414L, 2424L, 2438L, 2442L, 2450L, 2466L, 
    2466L, 2466L, 2495L, 2495L, 2495L, 2495L)), class = "data.frame", row.names = c(NA, 
-189L))
`./denim_abr.txt` <-
structure(list(Laundry = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L), Denim = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), Abrasion = c(3.2218, 
3.3547, 3.1334, 2.6289, 3.8816, 3.4383, 2.7742, 3.4454, 3.6696, 
3.1223, 3.1506, 3.03, 2.7948, 2.5685, 3.2388, 3.1351, 2.7016, 
2.842, 2.8887, 2.6499, 3.0114, 3.0123, 2.3802, 3.0909, 2.3173, 
2.1572, 1.6737, 1.2398, 2.4494, 2.6677, 2.2389, 2.4392, 2.0989, 
1.7627, 2.1132, 2.1229, 2.5048, 2.2467, 1.4007, 1.7422, 1.3373, 
2.0123, 1.9434, 2.019, 1.297, 1.88, 2.0632, 2.0151, 1.8988, 1.8638, 
1.717, 2.2421, 1.8357, 1.8986, 1.3799, 1.8926, 2.2674, 1.8818, 
1.5106, 1.7043, 2.679, 2.9687, 2.775, 3.0185, 2.2233, 2.4641, 
2.8179, 2.6048, 2.7132, 3.0655, 1.8032, 2.1526, 2.4623, 2.2728, 
1.8494, 2.4745, 2.0292, 3.4265, 1.3626, 2.8369, 1.5333, 1.8093, 
2.26, 1.9291, 2.6441, 1.6144, 2.5819, 3.1609, 2.1734, 2.9636)), class = "data.frame", row.names = c(NA, 
-90L))
`./Drugprice.txt` <-
structure(list(OriginatorMPR = c(3.32, 2.7, 32.09, 5.04, 33.98, 
14.54, 49.48, 1.35, 23.74, 7.97, 9.92, 7.16, 58.86), GenericMPR = c(1.43, 
1.2, 6.06, 1.28, 5.28, 3.07, 11.22, 0.11, 2.71, 2.63, 3.95, 3.93, 
5.32)), class = "data.frame", row.names = c(NA, -13L))
`./Girlgrowth.txt` <-
structure(list(Age = c(7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L), Height = c(115.1, 119.3, 117.2, 120.8, 
123, 122, 118, 113.5, 120.7, 110.6, 120.5, 120.6, 124.2, 122.1, 
119, 129, 114.1, 115.6, 108.7, 109.8, 120.6, 117.1, 117.1, 119.9, 
113.6, 108.9, 116.7, 118.1, 128, 120.1, 117.5, 117.6, 117.3, 
118.2, 117.9, 114.1, 116.3, 121.9, 123.5, 116.1, 114.3, 112.1, 
122.7, 114.5, 116.5, 108.8, 120.1, 107.7, 112.7, 119.9, 120.5, 
126.7, 127.8, 121.8, 124.5, 112.4, 121.3, 120.1, 116, 109.9, 
123.2, 108.7, 109.7, 119.7, 123.4, 124, 113.5, 116.7, 114.4, 
107.7, 116, 121.9, 121.2, 125.8, 115.4, 115.9, 119.9, 110.6, 
117.9, 118.6, 109.9, 115.4, 129.5, 116, 114.3, 117, 120.6, 116.2, 
119.2, 117.5, 115.4, 122.2, 116.6, 109.8, 116, 126.8, 128.2, 
118.3, 112.8, 109.8, 112.8, 124.5, 128.1, 115.4, 119.5, 111.9, 
119.2, 117.7, 118.7, 119.1, 125, 112.7, 125.2, 120.6, 117, 114.1, 
113, 116, 119.4, 117.9, 110.9, 118.2, 114.3, 116.1, 115.5, 122.3, 
115.9, 117.1, 112.1, 123.9, 130.6, 123.1, 123.5, 127.1, 111.8, 
113.1, 118.1, 116.8, 117.3, 114.4, 110.8, 119.3, 123.2, 119.5, 
116.9, 123.6, 120.1, 123, 123.8, 127.3, 116.9, 130.7, 120.9, 
120.6, 120.5, 128.6, 135.2, 135.7, 123.3, 111.4, 120.6, 126.7, 
125.7, 133.2, 127.3, 119.5, 123.4, 120.4, 130.3, 120.6, 130, 
125.1, 127.5, 127.4, 122.6, 135.1, 121.6, 131.3, 120.6, 131.6, 
129.8, 134.5, 125.1, 122.2, 132.1, 118.9, 136.7, 128.7, 123.1, 
123, 119.8, 130.1, 135.9, 120, 120.1, 128.1, 128.9, 128.1, 131.8, 
135.9, 121.5, 123.6, 128.3, 122.6, 116, 122.3, 122.6, 119.1, 
120.5, 129.9, 115.5, 124.2, 121.1, 133.9, 121.4, 125, 120.3, 
136.1, 122.3, 117.1, 125.3, 122.5, 122.8, 130.2, 125.4, 127.6, 
113.2, 119.4, 127.3, 120.9, 122.4, 122.7, 115.6, 124.1, 127.5, 
124.3, 129.7, 123.3, 124.3, 131.7, 126.4, 127.6, 133.9, 122.4, 
125.7, 121.7, 119.9, 122.6, 122.2, 127.1, 115.5, 121.2, 124.2, 
112.5, 121.7, 131.1, 130.3, 132.3, 131.4, 128.6, 137, 122.1, 
124, 122.9, 115.5, 121.1, 120.3, 128.3, 124.6, 112.4, 121, 119.3, 
125.7, 119.8, 117.7, 119.5, 117.2, 128.6, 129.7, 122.8, 123, 
129.9, 123.8, 126.4, 123, 124.7, 120.4, 122.1, 119.5, 128, 122, 
117.4, 125.5, 121.7, 113, 124.3, 123.4, 116.8, 129.6, 129.8, 
129.3, 126.4, 129.8, 119.1, 124, 126.9, 131.5, 128.5, 112, 146.4, 
122.8, 133, 126.4, 134.4, 130.4, 134.5, 149.4, 131.4, 135.9, 
132, 135.6, 135.6, 134.2, 120.6, 125.2, 132, 123.8, 135.4, 128.6, 
132.2, 121, 134.3, 136.8, 131.6, 133.1, 130.1, 132.4, 125.6, 
131.2, 135.9, 146, 125.7, 138.1, 126.7, 119.9, 135.5, 133.9, 
117.5, 130.8, 149.4, 135.5, 136, 127.1, 137.5, 138.3, 124.9, 
129.6, 136.3, 132, 120.4, 147.2, 130.8, 121, 127.5, 141.7, 130.1, 
128.8, 138.8, 127.4, 142.8, 131.9, 133.4, 127.5, 128.6, 131.9, 
117.1, 127.3, 129.3, 125.1, 131.4, 134.6, 130.7, 139.4, 129.5, 
131.4, 124.5, 140.1, 132.7, 126.3, 139.1, 133.9, 125, 134, 131.8, 
130.4, 128.4, 130.1, 123.7, 127.9, 137.4, 116.9, 126.4, 119.6, 
115.9, 116.6, 145.7, 131.3, 139.4, 131.3, 128, 134.4, 126.4, 
129.8, 125.2, 123.7, 122.6, 132.7, 127.1, 133.8, 121.6, 137.6, 
120.3, 130.6, 122.6, 128.8, 128.6, 130.2, 144.7, 136.9, 124.5, 
130.1, 136.6, 126.3, 127.3, 131.6, 134.7, 123.5, 128, 133.8, 
132.6, 134.6, 130.3, 132, 132, 129.1, 129.1, 141.7, 129.7, 127.3, 
132.2, 135.1, 138.4, 145, 135.2, 143.5, 132.8, 134.6, 136.3, 
131, 140.5, 130.9, 138.1, 146.5, 134.3, 130.8, 142.2, 140, 129.8, 
144.1, 139.5, 131.4, 128, 139.6, 139.7, 149.7, 134.4, 142.2, 
141.4, 138.9, 134.7, 141, 144.7, 129.9, 138.8, 143.8, 142.9, 
132.2, 150, 154.1, 129.5, 142.8, 142.1, 134.6, 135.4, 139.2, 
134.9, 136.4, 134.2, 139.4, 128.9, 137.8, 128.4, 136, 135.3, 
131.7, 131, 137.8, 132.7, 140.9, 138.6, 149.1, 143.4, 141.9, 
146.6, 138.9, 141.7, 147.4, 144, 130.1, 130.5, 136.9, 130.7, 
140.2, 131.3, 140.7, 138.7, 128.3, 140, 133.2, 142.3, 137, 133.1, 
144.5, 131.4, 134.7, 131.4, 132.8, 144.9, 139.8, 137, 144.4, 
127.5, 132.4, 148.7, 124.4, 134.9, 127.7, 145.1, 128.8, 133.3, 
123.2, 132.6, 128.1, 133.7, 130.5, 137.9, 128.2, 131.7, 145.9, 
138.6, 134.1, 136.6, 130, 132.3, 137.4, 133.4, 127.9, 136.7, 
143.8, 133.1, 144.5, 143.6, 136.2, 137.2, 138.6, 138.9, 132.6, 
140.2, 146.2, 143.4, 136.8, 132.6, 137.7, 132.8, 144, 145, 133.1, 
139.2, 145.6, 142, 143.8, 134.4, 146.1, 137.8, 122.8, 131, 142.9, 
151.6, 133.4, 130.8, 129.8, 140, 138.4, 144.4, 131, 145.1, 133.1, 
137, 134.7, 134.7, 137.5, 133.6, 132.5, 146.7, 139.5, 130.5, 
139.2, 127.5, 133.7, 145.5, 144.2, 136.5, 137.3, 140.8, 136.4, 
133.9, 148.2, 139.3, 134.8, 146.6, 146.6, 147.8, 152.9, 152.6, 
141.6, 140.1, 144.4, 140.6, 144.5, 143.2, 143.3, 145.5, 138.2, 
146.1, 140.6, 146.1, 139.2, 132.8, 144.4, 133.4, 131.9, 133.3, 
141.2, 139.3, 148.1, 141.2, 145.7, 143.8, 152.4, 155, 150.5, 
140.6, 141.2, 138.4, 145.9, 132.3, 153.5, 141.8, 136.5, 138.4, 
140.7, 147.6, 143.8, 152.6, 135.5, 147.4, 133.2, 148.9, 135.9, 
137, 155.4, 137.6, 140.4, 138.4, 141.5, 143.3, 136, 139.8, 129.2, 
146.9, 148.1, 139, 126.8, 143.9, 149, 144.8, 145.4, 151.4, 122.5, 
152.6, 143, 142.1, 139.8, 150.2, 130.4, 137.6, 145, 148.5, 147.6, 
133.7, 153.1, 144.4, 145, 134.3, 142.2, 139.6, 133.7, 130, 150.7, 
145, 144.6, 136.8, 129.6, 149.5, 142.8, 147.7, 135.2, 145.2, 
137.6, 136, 146.4, 150, 129.4, 135.4, 154, 141.8, 146.4, 155.7, 
144, 138.6, 142.8, 137.9, 145.7, 133, 150, 149.7, 141.6, 138.7, 
139.7, 150.9, 150.6, 152.2, 129.5, 132.5, 155.3, 138.4, 134.6, 
143.9, 141.4, 149.4, 145.9, 137.8, 150.9, 147.1, 133.7, 144.2, 
143.2, 148.4, 136.3, 142.4, 155.8, 155.2, 151.5, 147.2, 141.4, 
140.7, 138.6, 157.2, 152.7, 145.5, 141.4, 146.9, 142.3, 147, 
143.5, 135.9, 144.6, 146.2, 140.9, 146, 152.7, 153.4, 127.2, 
126, 156.3, 151.5, 141.9, 138, 161.1, 145.5, 152, 144.6, 148.1, 
154.9, 148.2, 149, 141, 156.4, 135.9, 150.5, 157.1, 138.9, 150.5, 
148.8, 149.2, 152.8, 134.7, 152.7, 148.7, 149.1, 148.3, 132.7, 
146.3, 145.7, 145.1, 144.7, 133.6, 154.1, 149.9, 151.5, 151, 
147.9, 140.8, 137.5, 144.5, 144, 144.3, 146.3, 129, 148.7, 155.3, 
139.5, 153.8, 146.8, 136.3, 143, 155.7, 157, 149, 139.2, 144.6, 
152.3, 155.4, 150.2, 151.7, 149.9, 152.2, 164.1, 137.2, 150.3, 
149.9, 144.8, 144.6, 152.2, 139.8, 144.4, 156.6, 149.8, 155.5, 
155.7, 154.9, 137.4, 151.4, 143.1, 155.5, 155.4, 155.1, 142.5, 
144.7, 149.9, 153.7, 136.7, 146.6, 144.3, 148, 146.1, 152.7, 
146.1, 141.8, 146.8, 146.6, 149.5, 154, 140.5, 148, 147.1, 151.4, 
158.9, 152.8, 148.9, 143.5, 151.4, 151.5, 149.6, 156.7)), class = "data.frame", row.names = c(NA, 
-905L))
`./hiv.txt` <-
structure(list(Absorbance = c(1.053, 1.708, 0.977, 0.881, 0.788, 
0.788, 0.896, 1.038, 0.963, 0.971, 1.234, 1.089, 0.984, 0.986, 
1.067, 0.996, 1.129, 1.016, 1.019, 1.088, 1.28, 1.12, 1.054, 
1.235, 1.327, 1.361, 1.233, 1.079, 1.12, 0.959, 1.229, 1.027, 
1.109, 1.118, 1.066, 1.146, 1.053, 1.082, 1.113, 1.14, 1.172, 
0.966, 0.963, 1.064, 1.086, 0.985, 0.894, 1.019, 0.847, 0.799, 
0.918, 1.033, 0.943, 1.089, 0.988, 1.169, 1.106, 1.308, 1.498, 
1.271, 1.128, 1.141, 1.144, 0.99, 0.801, 0.416, 0.929, 0.95, 
0.899, 0.873, 0.871, 0.786, 0.93, 0.968, 0.844), Lot = c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), Run = c(1L, 1L, 1L, 
2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 2L, 
2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 2L, 2L, 
2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 2L, 2L, 2L, 
3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 
3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L)), class = "data.frame", row.names = c(NA, 
-75L))
`./hoop.txt` <-
structure(list(Temp = c(-20L, -20L, -20L, -20L, -20L, -20L, -20L, 
-20L, -20L, -20L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 20L, 
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 40L, 40L, 40L, 40L, 
40L, 40L, 40L, 40L, 40L, 40L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 
60L, 60L, 60L), Tree = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 
5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L), Strength = c(13.14, 
15.9, 13.39, 15.51, 15.53, 15.26, 15.06, 15.21, 16.9, 15.45, 
12.46, 14.11, 12.32, 13.68, 13.16, 13.64, 13.25, 13.54, 15.23, 
14.06, 9.43, 11.3, 9.65, 10.33, 10.29, 10.35, 10.56, 10.46, 11.94, 
10.74, 7.63, 9.56, 7.9, 8.27, 8.67, 8.67, 8.1, 8.3, 9.34, 7.75, 
6.34, 7.27, 6.41, 7.06, 6.68, 6.62, 6.15, 6.09, 6.26, 6.29), 
    Moisture = c(42.1, 41, 41.1, 41, 41, 42, 40.4, 39.3, 39.2, 
    37.7, 41.1, 39.4, 40.2, 39.8, 41.2, 40, 39, 38.8, 38.5, 35.7, 
    43.1, 40.3, 40.6, 40.4, 39.7, 40.3, 34.9, 37.5, 38.5, 36.7, 
    41.4, 38.6, 41.7, 39.8, 39, 40.9, 40.1, 40.6, 39.4, 38.9, 
    39.1, 36.7, 39.7, 39.3, 39, 41.2, 41.4, 41.8, 41.7, 38.2)), class = "data.frame", row.names = c(NA, 
-50L))
`./imf2015.txt` <-
structure(list(Country = structure(1:33, .Label = c("Australia", 
"Austria", "Belgium", "Canada", "Cyprus", "CzechRepublic", "Denmark", 
"Estonia", "Finland", "France", "Germany", "Greece", "Iceland", 
"Ireland", "Israel", "Italy", "Japan", "Korea", "Latvia", "Lithuania", 
"Luxembourg", "Netherlands", "NewZealand", "Norway", "Portugal", 
"Singapore", "SlovakRepublic", "Slovenia", "Spain", "Sweden", 
"Switzerland", "UnitedKingdom", "UnitedStates"), class = "factor"), 
    CAB = c(-4.732, 1.846, 0.442, -3.401, -2.914, 0.908, 9.155, 
    2.206, -0.416, -0.2, 8.328, 0.117, 5.471, 10.241, 4.348, 
    1.62, 3.094, 7.661, -0.775, -2.335, 5.241, 8.676, -3.363, 
    8.661, 0.069, 18.11, 0.213, 5.18, 1.369, 4.695, 11.525, -4.284, 
    -2.567), DEBT = c(37.626, 85.544, 105.761, 91.55, 107.533, 
    40.314, 39.554, 10.052, 63.663, 96.164, 71.151, 179.354, 
    68.05, 78.706, 64.082, 132.042, 237.968, 37.755, 34.837, 
    42.544, 22.091, 65.119, 29.557, 33.203, 128.988, 103.239, 
    52.495, 83.149, 99.772, 42.926, 45.802, 88.96, 105.607), 
    EXP = c(37.269, 51.607, 53.861, 40.251, 40.391, 41.975, 54.825, 
    40.365, 56.979, 56.981, 43.981, 51.199, 42.882, 29.473, 39.622, 
    50.449, 36.638, 20.923, 37.705, 34.413, 42.119, 45.195, 34.227, 
    47.974, 48.36, 18.316, 45.272, 44.083, 43.76, 48.919, 32.65, 
    40.129, 35.284), GDP = c(51363.897, 43749.552, 40520.104, 
    43349.618, 23105.397, 17569.893, 53237.279, 17111.301, 42487.05, 
    37612.91, 41197.411, 17955.191, 50472.936, 60896.183, 35743.461, 
    30032.106, 34513.355, 27105.076, 13614.467, 14259.6, 100950.492, 
    44322.826, 37281.09, 74264.426, 19225.674, 53628.762, 16105.126, 
    20746.898, 25717.563, 50319.105, 81410.024, 43976.416, 56174.941
    ), INFL = c(1.461, 0.81, 0.62, 1.132, -1.539, 0.335, 0.452, 
    0.068, -0.156, 0.09, 0.134, -1.094, 1.633, -0.017, -0.632, 
    0.108, 0.793, 0.706, 0.213, -0.677, 0.061, 0.22, 0.293, 2.171, 
    0.508, -0.523, -0.336, -0.526, -0.497, 0.702, -1.14, 0.05, 
    0.12), INV = c(26.304, 23.507, 23.211, 23.817, 13.956, 27.357, 
    19.755, 24.745, 21.144, 22.363, 19.243, 9.829, 19.081, 21.763, 
    19.948, 17.314, 23.896, 28.918, 22.091, 19.89, 19.625, 19.272, 
    22.747, 28.208, 15.451, 26.77, 23.202, 20.064, 20.06, 24.207, 
    22.995, 17.18, 20.348), UNMP = c(6.058, 5.75, 8.492, 6.9, 
    14.892, 5.046, 6.192, 6.104, 9.375, 10.367, 4.608, 24.9, 
    3.992, 9.442, 5.275, 11.908, 3.375, 3.642, 9.877, 9.119, 
    6.804, 6.891, 5.35, 4.374, 12.444, 1.9, 11.492, 9, 22.058, 
    7.4, 3.178, 5.4, 5.258)), class = "data.frame", row.names = c(NA, 
-33L))
`./Iris.txt` <-
structure(list(Species_No = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), Petal_width = c(2L, 
2L, 2L, 1L, 2L, 2L, 2L, 4L, 2L, 2L, 4L, 2L, 2L, 1L, 3L, 4L, 2L, 
2L, 2L, 2L, 1L, 2L, 4L, 1L, 2L, 4L, 2L, 2L, 1L, 2L, 4L, 3L, 3L, 
2L, 3L, 5L, 2L, 6L, 3L, 2L, 2L, 2L, 4L, 2L, 2L, 3L, 3L, 2L, 2L, 
2L, 13L, 16L, 14L, 12L, 10L, 10L, 15L, 10L, 14L, 12L, 15L, 13L, 
15L, 11L, 13L, 14L, 17L, 15L, 14L, 11L, 15L, 15L, 14L, 10L, 13L, 
13L, 16L, 10L, 13L, 10L, 12L, 13L, 15L, 13L, 14L, 15L, 18L, 16L, 
13L, 11L, 12L, 15L, 12L, 13L, 10L, 15L, 13L, 13L, 14L, 13L, 24L, 
23L, 20L, 19L, 17L, 19L, 18L, 21L, 19L, 18L, 15L, 23L, 20L, 18L, 
21L, 25L, 21L, 22L, 15L, 23L, 23L, 25L, 18L, 23L, 21L, 18L, 18L, 
23L, 18L, 20L, 25L, 18L, 22L, 21L, 13L, 20L, 20L, 14L, 18L, 24L, 
16L, 21L, 18L, 23L, 19L, 18L, 22L, 19L, 20L, 24L), Petal_length = c(14L, 
10L, 16L, 14L, 13L, 16L, 16L, 19L, 14L, 14L, 15L, 14L, 14L, 14L, 
17L, 15L, 13L, 13L, 16L, 12L, 11L, 14L, 16L, 15L, 15L, 17L, 13L, 
15L, 15L, 15L, 13L, 13L, 15L, 15L, 14L, 17L, 14L, 16L, 14L, 19L, 
12L, 14L, 15L, 15L, 15L, 13L, 14L, 16L, 17L, 15L, 45L, 47L, 47L, 
40L, 33L, 41L, 45L, 33L, 39L, 39L, 42L, 44L, 49L, 30L, 36L, 44L, 
50L, 45L, 46L, 39L, 45L, 45L, 44L, 35L, 42L, 42L, 45L, 35L, 54L, 
50L, 47L, 41L, 49L, 40L, 48L, 46L, 48L, 51L, 40L, 38L, 44L, 45L, 
42L, 56L, 37L, 47L, 41L, 43L, 47L, 40L, 56L, 51L, 52L, 51L, 45L, 
50L, 49L, 56L, 51L, 55L, 50L, 57L, 49L, 58L, 54L, 61L, 55L, 56L, 
51L, 59L, 54L, 57L, 51L, 53L, 57L, 60L, 49L, 61L, 48L, 51L, 60L, 
55L, 67L, 66L, 52L, 64L, 67L, 56L, 48L, 56L, 58L, 59L, 56L, 69L, 
61L, 63L, 58L, 53L, 50L, 51L), Sepal_width = c(33L, 36L, 31L, 
36L, 32L, 38L, 30L, 38L, 30L, 36L, 34L, 42L, 29L, 30L, 38L, 37L, 
35L, 30L, 32L, 32L, 30L, 35L, 34L, 41L, 31L, 39L, 32L, 34L, 31L, 
37L, 39L, 23L, 38L, 35L, 34L, 33L, 34L, 35L, 30L, 34L, 40L, 32L, 
44L, 34L, 31L, 35L, 35L, 34L, 34L, 37L, 28L, 33L, 32L, 26L, 23L, 
27L, 29L, 24L, 27L, 27L, 30L, 23L, 25L, 25L, 29L, 30L, 30L, 22L, 
30L, 25L, 32L, 30L, 31L, 26L, 26L, 27L, 34L, 20L, 29L, 22L, 28L, 
28L, 31L, 25L, 28L, 28L, 32L, 27L, 28L, 24L, 26L, 30L, 30L, 29L, 
24L, 31L, 30L, 29L, 29L, 23L, 31L, 31L, 30L, 27L, 25L, 25L, 27L, 
28L, 27L, 31L, 22L, 32L, 28L, 25L, 31L, 36L, 30L, 28L, 28L, 32L, 
34L, 33L, 30L, 32L, 33L, 32L, 30L, 30L, 30L, 32L, 33L, 30L, 38L, 
30L, 30L, 38L, 28L, 26L, 28L, 34L, 30L, 30L, 29L, 26L, 28L, 29L, 
30L, 27L, 25L, 28L), Sepal_length = c(50L, 46L, 48L, 49L, 44L, 
51L, 50L, 51L, 49L, 50L, 54L, 55L, 44L, 48L, 57L, 51L, 55L, 44L, 
47L, 50L, 43L, 51L, 50L, 52L, 49L, 54L, 47L, 51L, 49L, 54L, 54L, 
45L, 51L, 52L, 46L, 51L, 52L, 50L, 48L, 48L, 58L, 46L, 57L, 52L, 
46L, 50L, 51L, 48L, 54L, 53L, 57L, 63L, 70L, 58L, 50L, 58L, 60L, 
49L, 52L, 58L, 59L, 63L, 63L, 51L, 56L, 66L, 67L, 62L, 61L, 56L, 
64L, 54L, 67L, 57L, 57L, 56L, 60L, 50L, 62L, 60L, 61L, 57L, 69L, 
55L, 68L, 65L, 59L, 60L, 61L, 55L, 55L, 56L, 57L, 66L, 55L, 67L, 
56L, 64L, 61L, 55L, 67L, 69L, 65L, 58L, 49L, 63L, 63L, 64L, 58L, 
64L, 60L, 69L, 56L, 67L, 69L, 72L, 68L, 64L, 63L, 68L, 62L, 67L, 
59L, 64L, 67L, 72L, 61L, 77L, 60L, 65L, 63L, 65L, 77L, 76L, 67L, 
79L, 77L, 61L, 62L, 63L, 72L, 71L, 63L, 77L, 74L, 73L, 65L, 64L, 
57L, 58L), Species_name = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
), .Label = c("Setosa", "Verginica", "Versicolor"), class = "factor")), class = "data.frame", row.names = c(NA, 
-150L))
`./kinks.txt` <-
structure(list(beta = c(51L, 57L, 49L, 48L, 65L, 54L, 53L, 52L, 
51L, 54L, 47L, 53L, 46L, 49L, 52L, 40L, 46L, 51L, 50L, 47L, 50L, 
62L, 63L, 56L, 55L, 66L, 67L, 64L, 68L, 64L, 53L, 58L, 40L, 34L, 
39L, 60L, 44L, 60L, 55L, 58L, 68L, 43L, 46L, 50L, 47L, 40L, 47L, 
41L, 43L, 50L, 25L, 44L, 45L, 48L, 47L, 39L, 39L, 42L, 39L, 16L, 
61L, 41L, 50L, 48L, 43L, 52L, 47L, 45L, 53L, 49L, 51L, 40L, 28L, 
35L, 47L, 49L, 38L, 41L, 32L, 50L, 39L, 65L, 58L, 62L, 54L, 59L, 
62L, 50L, 60L, 55L, 52L, 64L, 60L, 63L, 64L, 58L, 60L, 60L, 58L, 
59L), order = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), type = c(1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L)), class = "data.frame", row.names = c(NA, 
-100L))
`./LAcrimeTemp.txt` <-
structure(list(Year = c(1975L, 1975L, 1975L, 1975L, 1975L, 1975L, 
1975L, 1975L, 1975L, 1975L, 1975L, 1975L, 1976L, 1976L, 1976L, 
1976L, 1976L, 1976L, 1976L, 1976L, 1976L, 1976L, 1976L, 1976L, 
1977L, 1977L, 1977L, 1977L, 1977L, 1977L, 1977L, 1977L, 1977L, 
1977L, 1977L, 1977L, 1978L, 1978L, 1978L, 1978L, 1978L, 1978L, 
1978L, 1978L, 1978L, 1978L, 1978L, 1978L, 1979L, 1979L, 1979L, 
1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 1979L, 
1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 1980L, 
1980L, 1980L, 1980L, 1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 
1981L, 1981L, 1981L, 1981L, 1981L, 1981L, 1982L, 1982L, 1982L, 
1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 1982L, 
1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 1983L, 
1983L, 1983L, 1983L, 1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 
1984L, 1984L, 1984L, 1984L, 1984L, 1984L, 1985L, 1985L, 1985L, 
1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 1985L, 
1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 1986L, 
1986L, 1986L, 1986L, 1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 
1987L, 1987L, 1987L, 1987L, 1987L, 1987L, 1988L, 1988L, 1988L, 
1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 1988L, 
1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 1989L, 
1989L, 1989L, 1989L, 1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 
1990L, 1990L, 1990L, 1990L, 1990L, 1990L, 1991L, 1991L, 1991L, 
1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 1991L, 
1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 1992L, 
1992L, 1992L, 1992L, 1993L, 1993L, 1993L, 1993L, 1993L, 1993L, 
1993L, 1993L, 1993L, 1993L, 1993L, 1993L), Month = c(1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 
6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L), Population = c(2729878L, 2729878L, 2729878L, 2729878L, 
2729878L, 2729878L, 2729878L, 2729878L, 2729878L, 2729878L, 2729878L, 
2729878L, 2739100L, 2739100L, 2739100L, 2739100L, 2739100L, 2739100L, 
2739100L, 2739100L, 2739100L, 2739100L, 2739100L, 2739100L, 2785393L, 
2785393L, 2785393L, 2785393L, 2785393L, 2785393L, 2785393L, 2785393L, 
2785393L, 2785393L, 2785393L, 2785393L, 2787525L, 2787525L, 2787525L, 
2787525L, 2787525L, 2787525L, 2787525L, 2787525L, 2787525L, 2787525L, 
2787525L, 2787525L, 2863412L, 2863412L, 2863412L, 2863412L, 2863412L, 
2863412L, 2863412L, 2863412L, 2863412L, 2863412L, 2863412L, 2863412L, 
2952511L, 2952511L, 2952511L, 2952511L, 2952511L, 2952511L, 2952511L, 
2952511L, 2952511L, 2952511L, 2952511L, 2952511L, 3031090L, 3031090L, 
3031090L, 3031090L, 3031090L, 3031090L, 3031090L, 3031090L, 3031090L, 
3031090L, 3031090L, 3031090L, 3101979L, 3101979L, 3101979L, 3101979L, 
3101979L, 3101979L, 3101979L, 3101979L, 3101979L, 3101979L, 3101979L, 
3101979L, 3158688L, 3158688L, 3158688L, 3158688L, 3158688L, 3158688L, 
3158688L, 3158688L, 3158688L, 3158688L, 3158688L, 3158688L, 3144256L, 
3144256L, 3144256L, 3144256L, 3144256L, 3144256L, 3144256L, 3144256L, 
3144256L, 3144256L, 3144256L, 3144256L, 3186459L, 3186459L, 3186459L, 
3186459L, 3186459L, 3186459L, 3186459L, 3186459L, 3186459L, 3186459L, 
3186459L, 3186459L, 3260856L, 3260856L, 3260856L, 3260856L, 3260856L, 
3260856L, 3260856L, 3260856L, 3260856L, 3260856L, 3260856L, 3260856L, 
3341726L, 3341726L, 3341726L, 3341726L, 3341726L, 3341726L, 3341726L, 
3341726L, 3341726L, 3341726L, 3341726L, 3341726L, 3402342L, 3402342L, 
3402342L, 3402342L, 3402342L, 3402342L, 3402342L, 3402342L, 3402342L, 
3402342L, 3402342L, 3402342L, 3441449L, 3441449L, 3441449L, 3441449L, 
3441449L, 3441449L, 3441449L, 3441449L, 3441449L, 3441449L, 3441449L, 
3441449L, 3485398L, 3485398L, 3485398L, 3485398L, 3485398L, 3485398L, 
3485398L, 3485398L, 3485398L, 3485398L, 3485398L, 3485398L, 3558316L, 
3558316L, 3558316L, 3558316L, 3558316L, 3558316L, 3558316L, 3558316L, 
3558316L, 3558316L, 3558316L, 3558316L, 3615355L, 3615355L, 3615355L, 
3615355L, 3615355L, 3615355L, 3615355L, 3615355L, 3615355L, 3615355L, 
3615355L, 3615355L, 3525317L, 3525317L, 3525317L, 3525317L, 3525317L, 
3525317L, 3525317L, 3525317L, 3525317L, 3525317L, 3525317L, 3525317L
), TempCelsius = c(13.8, 13.1, 13.2, 13.7, 16.2, 18.1, 20.5, 
20.2, 21.2, 18.6, 15.9, 14.3, 15.6, 14.4, 14.7, 14.4, 17.4, 20, 
21.2, 20.7, 21.3, 20.7, 18.8, 15.6, 14.2, 15.9, 13.3, 16.2, 16.2, 
18.4, 20.3, 21.6, 20.4, 19, 18.2, 16.1, 14.8, 14.6, 16.7, 15.1, 
18.6, 19.8, 19.8, 21, 23.1, 20.2, 15, 12.4, 12.6, 12.3, 14.2, 
15.7, 17.6, 20.7, 20.2, 21.7, 23.2, 18.9, 16.2, 15.9, 15.4, 16.3, 
14.6, 15.9, 15.6, 18.7, 20.4, 21.6, 19.4, 19, 16.9, 15.7, 15.3, 
15.9, 14.5, 16.2, 18.2, 22.2, 22.1, 21.8, 20.9, 18.5, 16.7, 15.2, 
12.6, 15.1, 14.2, 15.7, 16.9, 17.6, 20.7, 21.9, 22, 20.7, 16.2, 
13.5, 14.9, 14.1, 14.3, 15.1, 16.9, 18.6, 20.9, 23.1, 22.4, 20.8, 
16.1, 13.9, 14.6, 14.7, 16.3, 16.3, 18.9, 19.5, 21.8, 22.8, 24.7, 
18.7, 14.8, 12.9, 13.1, 13.7, 12.9, 15.9, 16.2, 18.9, 21.9, 21.1, 
20.4, 19.5, 14.8, 15.1, 16.8, 14.8, 15.1, 16.5, 17.4, 19.1, 20.3, 
20.5, 18.8, 19.1, 18.3, 14.7, 12.8, 14.6, 14.9, 17.3, 17.9, 18.2, 
19.1, 19.8, 20.9, 20.6, 16.6, 12.2, 13.7, 15.9, 16.9, 16.3, 17.2, 
17.6, 20.7, 20.2, 19.8, 18.9, 15.6, 13.6, 13, 12.7, 14.9, 18.2, 
16.9, 18.4, 20.8, 19.8, 20.2, 18.8, 18.4, 15.8, 13.9, 12.8, 14.2, 
16.9, 17.1, 19.7, 21.9, 20.9, 21.7, 20.9, 17.9, 13.8, 14, 15.5, 
12.8, 16.1, 15.7, 17.7, 19.4, 20.6, 19.9, 19.6, 17.4, 14.8, 14.7, 
16, 15.1, 18.7, 18.9, 18.8, 21.9, 22.7, 21.5, 19.4, 17.6, 13.2, 
13.4, 13.9, 15.8, 17.1, 18.4, 20.2, 20.8, 20.8, 20.6, 20.2, 17.6, 
14.7), Fahrenheit = c(56.84, 55.58, 55.76, 56.66, 61.16, 64.58, 
68.9, 68.36, 70.16, 65.48, 60.62, 57.74, 60.08, 57.92, 58.46, 
57.92, 63.32, 68, 70.16, 69.26, 70.34, 69.26, 65.84, 60.08, 57.56, 
60.62, 55.94, 61.16, 61.16, 65.12, 68.54, 70.88, 68.72, 66.2, 
64.76, 60.98, 58.64, 58.28, 62.06, 59.18, 65.48, 67.64, 67.64, 
69.8, 73.58, 68.36, 59, 54.32, 54.68, 54.14, 57.56, 60.26, 63.68, 
69.26, 68.36, 71.06, 73.76, 66.02, 61.16, 60.62, 59.72, 61.34, 
58.28, 60.62, 60.08, 65.66, 68.72, 70.88, 66.92, 66.2, 62.42, 
60.26, 59.54, 60.62, 58.1, 61.16, 64.76, 71.96, 71.78, 71.24, 
69.62, 65.3, 62.06, 59.36, 54.68, 59.18, 57.56, 60.26, 62.42, 
63.68, 69.26, 71.42, 71.6, 69.26, 61.16, 56.3, 58.82, 57.38, 
57.74, 59.18, 62.42, 65.48, 69.62, 73.58, 72.32, 69.44, 60.98, 
57.02, 58.28, 58.46, 61.34, 61.34, 66.02, 67.1, 71.24, 73.04, 
76.46, 65.66, 58.64, 55.22, 55.58, 56.66, 55.22, 60.62, 61.16, 
66.02, 71.42, 69.98, 68.72, 67.1, 58.64, 59.18, 62.24, 58.64, 
59.18, 61.7, 63.32, 66.38, 68.54, 68.9, 65.84, 66.38, 64.94, 
58.46, 55.04, 58.28, 58.82, 63.14, 64.22, 64.76, 66.38, 67.64, 
69.62, 69.08, 61.88, 53.96, 56.66, 60.62, 62.42, 61.34, 62.96, 
63.68, 69.26, 68.36, 67.64, 66.02, 60.08, 56.48, 55.4, 54.86, 
58.82, 64.76, 62.42, 65.12, 69.44, 67.64, 68.36, 65.84, 65.12, 
60.44, 57.02, 55.04, 57.56, 62.42, 62.78, 67.46, 71.42, 69.62, 
71.06, 69.62, 64.22, 56.84, 57.2, 59.9, 55.04, 60.98, 60.26, 
63.86, 66.92, 69.08, 67.82, 67.28, 63.32, 58.64, 58.46, 60.8, 
59.18, 65.66, 66.02, 65.84, 71.42, 72.86, 70.7, 66.92, 63.68, 
55.76, 56.12, 57.02, 60.44, 62.78, 65.12, 68.36, 69.44, 69.44, 
69.08, 68.36, 63.68, 58.46), Homicide = c(51L, 44L, 49L, 35L, 
44L, 37L, 49L, 46L, 47L, 57L, 48L, 47L, 49L, 34L, 38L, 33L, 51L, 
46L, 28L, 45L, 44L, 42L, 40L, 51L, 52L, 40L, 37L, 61L, 33L, 55L, 
38L, 45L, 49L, 36L, 60L, 70L, 32L, 34L, 63L, 40L, 51L, 52L, 51L, 
62L, 71L, 51L, 90L, 54L, 60L, 55L, 59L, 56L, 69L, 59L, 56L, 75L, 
57L, 77L, 69L, 94L, 67L, 62L, 58L, 82L, 68L, 95L, 95L, 122L, 
97L, 86L, 85L, 93L, 61L, 72L, 64L, 68L, 67L, 78L, 95L, 82L, 72L, 
84L, 65L, 71L, 72L, 47L, 83L, 70L, 72L, 71L, 69L, 69L, 100L, 
65L, 58L, 73L, 75L, 45L, 65L, 77L, 82L, 54L, 64L, 71L, 65L, 78L, 
79L, 65L, 69L, 49L, 57L, 63L, 68L, 54L, 62L, 81L, 71L, 68L, 69L, 
48L, 54L, 77L, 71L, 58L, 65L, 51L, 72L, 77L, 57L, 56L, 67L, 72L, 
59L, 55L, 81L, 72L, 62L, 57L, 73L, 85L, 90L, 71L, 67L, 62L, 69L, 
65L, 71L, 77L, 59L, 62L, 62L, 68L, 70L, 67L, 66L, 75L, 64L, 55L, 
53L, 55L, 57L, 51L, 78L, 65L, 74L, 69L, 53L, 62L, 85L, 63L, 64L, 
61L, 63L, 78L, 70L, 73L, 95L, 74L, 63L, 88L, 78L, 79L, 71L, 78L, 
69L, 70L, 109L, 115L, 92L, 88L, 62L, 72L, 71L, 48L, 72L, 86L, 
75L, 105L, 97L, 122L, 96L, 86L, 72L, 97L, 76L, 74L, 82L, 97L, 
69L, 72L, 115L, 119L, 103L, 100L, 97L, 90L, 94L, 79L, 87L, 76L, 
95L, 101L, 104L, 94L, 92L, 92L, 95L, 67L), Rape = c(140L, 154L, 
137L, 142L, 168L, 156L, 173L, 124L, 126L, 153L, 142L, 153L, 189L, 
129L, 138L, 162L, 166L, 147L, 228L, 203L, 172L, 198L, 173L, 142L, 
167L, 197L, 191L, 196L, 179L, 191L, 203L, 193L, 162L, 203L, 251L, 
206L, 158L, 199L, 200L, 203L, 221L, 206L, 216L, 189L, 244L, 237L, 
205L, 189L, 199L, 167L, 200L, 192L, 192L, 213L, 208L, 239L, 206L, 
218L, 244L, 230L, 239L, 239L, 224L, 235L, 200L, 228L, 226L, 282L, 
238L, 254L, 239L, 209L, 216L, 191L, 184L, 198L, 227L, 235L, 241L, 
256L, 214L, 257L, 217L, 230L, 209L, 175L, 244L, 218L, 264L, 202L, 
235L, 284L, 228L, 225L, 194L, 228L, 196L, 193L, 205L, 215L, 199L, 
192L, 218L, 242L, 223L, 228L, 175L, 208L, 183L, 174L, 185L, 170L, 
217L, 196L, 211L, 256L, 215L, 184L, 195L, 161L, 179L, 141L, 205L, 
216L, 197L, 175L, 219L, 209L, 207L, 173L, 193L, 204L, 190L, 145L, 
187L, 143L, 171L, 187L, 164L, 365L, 196L, 211L, 201L, 170L, 205L, 
185L, 207L, 183L, 197L, 196L, 171L, 156L, 189L, 183L, 153L, 144L, 
172L, 134L, 159L, 156L, 192L, 186L, 208L, 185L, 156L, 173L, 147L, 
138L, 168L, 151L, 160L, 180L, 184L, 152L, 177L, 140L, 163L, 159L, 
195L, 167L, 138L, 130L, 150L, 167L, 190L, 192L, 189L, 197L, 177L, 
192L, 157L, 135L, 137L, 136L, 153L, 185L, 158L, 174L, 197L, 158L, 
190L, 193L, 147L, 138L, 163L, 139L, 186L, 173L, 151L, 144L, 177L, 
178L, 173L, 137L, 127L, 124L, 131L, 118L, 145L, 149L, 166L, 167L, 
167L, 161L, 140L, 181L, 121L, 127L)), class = "data.frame", row.names = c(NA, 
-228L))
`./leprosy.txt` <-
structure(list(treatment = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("A", "D", "F"), class = "factor"), 
    pre = c(11L, 8L, 5L, 14L, 19L, 6L, 10L, 6L, 11L, 3L, 6L, 
    6L, 7L, 8L, 18L, 8L, 19L, 8L, 5L, 15L, 16L, 13L, 11L, 9L, 
    21L, 16L, 12L, 12L, 7L, 12L), post = c(6L, 0L, 2L, 8L, 11L, 
    4L, 13L, 1L, 8L, 0L, 0L, 2L, 3L, 1L, 18L, 4L, 14L, 9L, 1L, 
    9L, 13L, 10L, 18L, 5L, 23L, 12L, 5L, 16L, 1L, 20L)), class = "data.frame", row.names = c(NA, 
-30L))
`./Lifelength.txt` <-
structure(list(Category = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L), Lifelength = c(35L, 40L, 
44L, 48L, 50L, 52L, 53L, 56L, 56L, 56L, 57L, 57L, 57L, 59L, 62L, 
63L, 63L, 63L, 64L, 65L, 65L, 66L, 67L, 68L, 70L, 72L, 73L, 73L, 
74L, 74L, 74L, 76L, 76L, 76L, 77L, 78L, 78L, 79L, 80L, 80L, 81L, 
81L, 83L, 83L, 85L, 87L, 90L, 21L, 21L, 22L, 24L, 24L, 27L, 29L, 
29L, 29L, 30L, 30L, 31L, 32L, 32L, 32L, 32L, 33L, 33L, 33L, 33L, 
33L, 33L, 36L, 36L, 36L, 36L, 36L, 37L, 37L, 37L, 37L, 38L, 38L, 
38L, 40L, 40L, 40L, 41L, 41L, 41L, 42L, 43L, 43L, 43L, 44L, 44L, 
44L, 44L, 44L, 45L, 45L, 45L, 45L, 46L, 46L, 46L, 46L, 46L, 46L, 
46L, 46L, 47L, 47L, 47L, 47L, 48L, 48L, 48L, 48L, 49L, 49L, 49L, 
49L, 49L, 50L, 50L, 50L, 51L, 51L, 51L, 51L, 51L, 52L, 52L, 52L, 
53L, 53L, 53L, 53L, 53L, 54L, 54L, 54L, 54L, 55L, 55L, 55L, 56L, 
56L, 56L, 56L, 56L, 56L, 56L, 56L, 57L, 57L, 57L, 57L, 57L, 57L, 
58L, 58L, 58L, 58L, 59L, 59L, 60L, 60L, 60L, 61L, 61L, 61L, 62L, 
62L, 63L, 63L, 63L, 63L, 64L, 64L, 64L, 64L, 64L, 65L, 65L, 65L, 
65L, 65L, 65L, 65L, 66L, 66L, 67L, 67L, 67L, 68L, 68L, 68L, 68L, 
68L, 68L, 68L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 70L, 70L, 
70L, 70L, 70L, 71L, 71L, 71L, 72L, 72L, 72L, 72L, 72L, 72L, 73L, 
73L, 73L, 73L, 74L, 74L, 75L, 75L, 76L, 76L, 76L, 76L, 76L, 76L, 
76L, 76L, 77L, 77L, 77L, 77L, 78L, 78L, 78L, 78L, 79L, 79L, 80L, 
80L, 80L, 80L, 81L, 81L, 82L, 83L, 84L, 84L, 84L, 84L, 85L, 85L, 
85L, 85L, 85L, 86L, 86L, 87L, 90L, 115L, 29L, 34L, 35L, 37L, 
38L, 40L, 40L, 40L, 40L, 44L, 45L, 46L, 47L, 48L, 48L, 49L, 49L, 
49L, 51L, 52L, 52L, 53L, 53L, 53L, 53L, 53L, 54L, 54L, 54L, 55L, 
56L, 56L, 56L, 58L, 58L, 58L, 58L, 58L, 58L, 60L, 60L, 60L, 60L, 
60L, 60L, 61L, 61L, 62L, 63L, 63L, 63L, 63L, 64L, 64L, 64L, 64L, 
64L, 65L, 65L, 65L, 66L, 67L, 67L, 68L, 68L, 68L, 68L, 68L, 69L, 
69L, 69L, 69L, 70L, 70L, 70L, 70L, 71L, 71L, 72L, 74L, 74L, 75L, 
75L, 75L, 75L, 75L, 75L, 76L, 77L, 77L, 78L, 78L, 78L, 78L, 79L, 
80L, 81L, 82L, 82L, 82L, 83L, 84L, 85L, 85L, 86L, 87L, 88L, 90L, 
91L, 93L, 96L, 37L, 42L, 43L, 50L, 50L, 54L, 58L, 59L, 60L, 60L, 
62L, 62L, 63L, 63L, 63L, 65L, 68L, 68L, 69L, 69L, 70L, 70L, 71L, 
71L, 72L, 73L, 73L, 73L, 73L, 75L, 75L, 76L, 76L, 76L, 77L, 80L, 
80L, 81L, 83L, 84L, 86L, 88L, 90L, 91L, 96L, 22L, 26L, 28L, 34L, 
36L, 36L, 37L, 39L, 39L, 40L, 40L, 42L, 44L, 45L, 46L, 47L, 47L, 
48L, 48L, 49L, 50L, 50L, 51L, 52L, 54L, 55L, 56L, 57L, 57L, 57L, 
57L, 58L, 59L, 61L, 61L, 62L, 63L, 64L, 64L, 64L, 65L, 65L, 66L, 
67L, 67L, 67L, 67L, 67L, 67L, 68L, 69L, 71L, 72L, 72L, 72L, 74L, 
74L, 75L, 75L, 76L, 76L, 77L, 78L, 79L, 79L, 80L, 81L, 81L, 81L, 
81L, 81L, 82L, 84L, 85L, 85L, 87L, 87L, 90L, 90L, 90L, 91L, 91L, 
54L, 54L, 55L, 55L, 60L, 61L, 63L, 64L, 64L, 65L, 66L, 66L, 67L, 
67L, 67L, 68L, 69L, 70L, 71L, 72L, 72L, 72L, 73L, 74L, 75L, 76L, 
77L, 78L, 78L, 79L, 79L, 81L, 82L, 82L, 82L, 84L, 84L, 84L, 85L, 
86L, 86L, 87L, 88L, 28L, 37L, 38L, 42L, 45L, 45L, 46L, 47L, 49L, 
53L, 56L, 60L, 60L, 61L, 61L, 62L, 62L, 62L, 62L, 63L, 63L, 64L, 
64L, 66L, 66L, 67L, 68L, 68L, 69L, 69L, 69L, 69L, 70L, 70L, 70L, 
70L, 71L, 72L, 72L, 72L, 72L, 73L, 73L, 74L, 75L, 75L, 76L, 76L, 
76L, 77L, 80L, 80L, 80L, 81L, 81L, 81L, 82L, 83L, 83L, 86L, 88L, 
91L, 92L, 40L, 44L, 44L, 47L, 48L, 49L, 49L, 55L, 56L, 56L, 58L, 
59L, 60L, 60L, 60L, 61L, 61L, 62L, 62L, 62L, 64L, 65L, 65L, 65L, 
66L, 66L, 66L, 66L, 67L, 68L, 69L, 69L, 70L, 70L, 70L, 70L, 71L, 
72L, 73L, 74L, 74L, 74L, 74L, 75L, 75L, 76L, 76L, 77L, 77L, 77L, 
77L, 77L, 78L, 78L, 78L, 79L, 80L, 80L, 80L, 80L, 82L, 82L, 83L, 
83L, 83L, 84L, 84L, 84L, 85L, 86L, 86L, 89L, 90L, 91L, 92L, 93L
)), class = "data.frame", row.names = c(NA, -690L))
`./olympic.txt` <-
structure(list(Year = c(1900L, 1904L, 1908L, 1912L, 1920L, 1924L, 
1928L, 1932L, 1936L, 1948L, 1952L, 1956L, 1960L, 1964L, 1968L, 
1972L, 1976L, 1980L, 1984L, 1988L), X100m = c(10.8, 11, 10.8, 
10.8, 10.8, 10.6, 10.8, 10.3, 10.3, 10.3, 10.4, 10.5, 10.2, 10, 
9.95, 10.14, 10.06, 10.25, 9.99, 9.92), X200m = c(22.2, 21.6, 
22.4, 21.7, 22, 21.6, 21.8, 21.2, 20.7, 21.1, 20.7, 20.6, 20.5, 
20.3, 19.83, 20, 20.23, 20.19, 19.8, 19.75), X400m = c(49.4, 
49.2, 50, 48.2, 49.6, 47.6, 47.8, 46.2, 46.5, 46.2, 45.9, 46.7, 
44.9, 45.1, 43.8, 44.66, 44.26, 44.6, 44.27, 43.87), X800m = c(121.4, 
116, 112.8, 111.9, 113.4, 112.4, 111.8, 109.8, 112.9, 109.2, 
109.2, 107.7, 106.3, 105.1, 104.3, 105.9, 103.5, 105.4, 103, 
103.45), X1500m = c(246, 245.4, 243.4, 236.8, 241.8, 233.6, 233.2, 
231.2, 227.8, 225.2, 225.2, 221.2, 215.6, 218.1, 214.9, 216.3, 
219.2, 218.4, 212.5, 215.96)), class = "data.frame", row.names = c(NA, 
-20L))
`./poison.txt` <-
structure(list(Survtime = c(3.1, 4.5, 4.6, 4.3, 8.2, 11, 8.8, 
7.2, 4.3, 4.5, 6.3, 7.6, 4.5, 7.1, 6.6, 6.2, 3.6, 2.9, 4, 2.3, 
9.2, 6.1, 4.9, 12.4, 4.4, 3.5, 3.1, 4, 5.6, 10.2, 7.1, 3.8, 2.2, 
2.1, 1.8, 2.3, 3, 3.7, 3.8, 2.9, 2.3, 2.5, 2.4, 2.2, 3, 3.6, 
3.1, 3.3), Treatment = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 4L, 4L, 4L, 4L), Poison = c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L)), class = "data.frame", row.names = c(NA, 
-48L))
`./skulls.txt` <-
structure(list(MB = c(131L, 125L, 131L, 119L, 136L, 138L, 139L, 
125L, 131L, 134L, 129L, 134L, 126L, 132L, 141L, 131L, 135L, 132L, 
139L, 132L, 126L, 135L, 134L, 128L, 130L, 138L, 128L, 127L, 131L, 
124L, 124L, 133L, 138L, 148L, 126L, 135L, 132L, 133L, 131L, 133L, 
133L, 131L, 131L, 138L, 130L, 131L, 138L, 123L, 130L, 134L, 137L, 
126L, 135L, 129L, 134L, 131L, 132L, 130L, 135L, 130L, 137L, 129L, 
132L, 130L, 134L, 140L, 138L, 136L, 136L, 126L, 137L, 137L, 136L, 
137L, 129L, 135L, 129L, 134L, 138L, 136L, 132L, 133L, 138L, 130L, 
136L, 134L, 136L, 133L, 138L, 138L, 137L, 141L, 141L, 135L, 133L, 
131L, 140L, 139L, 140L, 138L, 132L, 134L, 135L, 133L, 136L, 134L, 
131L, 129L, 136L, 131L, 139L, 144L, 141L, 130L, 133L, 138L, 131L, 
136L, 132L, 135L, 137L, 136L, 128L, 130L, 138L, 126L, 136L, 126L, 
132L, 139L, 143L, 141L, 135L, 137L, 142L, 139L, 138L, 137L, 133L, 
145L, 138L, 131L, 143L, 134L, 132L, 137L, 129L, 140L, 147L, 136L
), BH = c(138L, 131L, 132L, 132L, 143L, 137L, 130L, 136L, 134L, 
134L, 138L, 121L, 129L, 136L, 140L, 134L, 137L, 133L, 136L, 131L, 
133L, 135L, 124L, 134L, 130L, 135L, 132L, 129L, 136L, 138L, 138L, 
134L, 134L, 129L, 124L, 136L, 145L, 130L, 134L, 125L, 136L, 139L, 
136L, 134L, 136L, 128L, 129L, 131L, 129L, 130L, 136L, 131L, 136L, 
126L, 139L, 134L, 130L, 132L, 132L, 128L, 141L, 133L, 138L, 134L, 
134L, 133L, 138L, 145L, 131L, 136L, 129L, 139L, 126L, 133L, 142L, 
138L, 135L, 125L, 134L, 135L, 130L, 131L, 137L, 127L, 133L, 123L, 
137L, 131L, 133L, 133L, 134L, 128L, 130L, 131L, 120L, 135L, 137L, 
130L, 134L, 140L, 133L, 134L, 135L, 136L, 130L, 137L, 141L, 135L, 
128L, 125L, 130L, 124L, 131L, 131L, 128L, 126L, 142L, 138L, 136L, 
130L, 123L, 131L, 126L, 134L, 127L, 138L, 138L, 126L, 132L, 135L, 
120L, 136L, 135L, 134L, 135L, 134L, 125L, 135L, 125L, 129L, 136L, 
129L, 126L, 124L, 127L, 125L, 128L, 135L, 129L, 133L), BL = c(89L, 
92L, 99L, 96L, 100L, 89L, 108L, 93L, 102L, 99L, 95L, 95L, 109L, 
100L, 100L, 97L, 103L, 93L, 96L, 101L, 102L, 103L, 93L, 103L, 
104L, 100L, 93L, 106L, 114L, 101L, 101L, 97L, 98L, 104L, 95L, 
98L, 100L, 102L, 96L, 94L, 103L, 98L, 99L, 98L, 104L, 98L, 107L, 
101L, 105L, 93L, 106L, 100L, 97L, 91L, 101L, 90L, 104L, 93L, 
98L, 101L, 96L, 93L, 87L, 106L, 96L, 98L, 95L, 99L, 92L, 95L, 
100L, 97L, 101L, 90L, 104L, 102L, 92L, 90L, 96L, 94L, 91L, 100L, 
94L, 99L, 91L, 95L, 101L, 96L, 100L, 91L, 107L, 95L, 87L, 99L, 
91L, 90L, 94L, 90L, 90L, 100L, 90L, 97L, 99L, 95L, 99L, 93L, 
99L, 95L, 93L, 88L, 94L, 86L, 97L, 98L, 92L, 97L, 95L, 94L, 92L, 
100L, 91L, 95L, 91L, 92L, 86L, 101L, 97L, 92L, 99L, 92L, 95L, 
101L, 95L, 93L, 96L, 95L, 99L, 96L, 92L, 89L, 92L, 97L, 88L, 
91L, 97L, 85L, 81L, 103L, 87L, 97L), NH = c(49L, 48L, 50L, 44L, 
54L, 56L, 48L, 48L, 51L, 51L, 50L, 53L, 51L, 50L, 51L, 54L, 50L, 
53L, 50L, 49L, 51L, 47L, 53L, 50L, 49L, 55L, 53L, 48L, 54L, 46L, 
48L, 48L, 45L, 51L, 45L, 52L, 54L, 48L, 50L, 46L, 53L, 51L, 56L, 
49L, 53L, 45L, 53L, 51L, 47L, 54L, 49L, 48L, 52L, 50L, 49L, 53L, 
50L, 52L, 54L, 51L, 52L, 47L, 48L, 50L, 45L, 50L, 47L, 55L, 46L, 
56L, 53L, 50L, 50L, 49L, 47L, 55L, 50L, 60L, 51L, 53L, 52L, 50L, 
51L, 45L, 49L, 52L, 54L, 49L, 55L, 46L, 54L, 53L, 49L, 51L, 46L, 
50L, 60L, 48L, 51L, 52L, 53L, 54L, 50L, 52L, 55L, 52L, 55L, 47L, 
54L, 48L, 53L, 50L, 53L, 53L, 51L, 54L, 53L, 55L, 52L, 51L, 50L, 
49L, 57L, 52L, 47L, 52L, 58L, 45L, 55L, 54L, 51L, 54L, 56L, 53L, 
52L, 47L, 51L, 54L, 50L, 47L, 46L, 44L, 54L, 55L, 52L, 57L, 52L, 
48L, 48L, 51L), Year = c(-4000L, -4000L, -4000L, -4000L, -4000L, 
-4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, 
-4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, 
-4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, -4000L, 
-4000L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, 
-3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, 
-3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, 
-3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -3300L, -1850L, 
-1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, 
-1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, 
-1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, -1850L, 
-1850L, -1850L, -1850L, -1850L, -1850L, -200L, -200L, -200L, 
-200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, 
-200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, 
-200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, -200L, 
150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 
150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L, 
150L, 150L, 150L, 150L, 150L, 150L, 150L, 150L)), class = "data.frame", row.names = c(NA, 
-150L))
`./splett2.txt` <-
structure(list(Energy = c(67.4, 65.5, 72, 73.6, 65.2, 67, 66.3, 
67.9, 65.8, 69.9, 64.5, 66, 66.8, 67, 69.9, 70.1, 69.7, 68.3, 
67, 68.2, 65, 66.6, 65.4, 68.1, 69, 66.2, 70, 68.5, 66, 67.5, 
68.5, 66.5, 73, 69, 69, 74.5, 68, 68.5, 67.5, 70, 69, 72.5, 68, 
69, 69, 71, 68, 75, 67, 73, 78.9, 75, 72.3, 72.4, 74.1, 72, 72, 
70.9, 74.5, 72, 72.5, 72.4, 74, 75, 70.9, 70.9, 76.6, 74.2, 69.5, 
68.8, 68.5, 70.1, 73, 70.9, 67.6, 64.2, 65.9, 65.9, 68.2, 71.1, 
67.6, 71.6, 72.8, 68.2, 67.6, 67.1, 67.1, 68.2, 65.4, 66.5, 67.6, 
67.1, 71.1, 67.1, 65.4, 67.6, 67.6, 70.5, 70.5), Machine = c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L)), class = "data.frame", row.names = c(NA, -99L))
`./stars1.txt` <-
structure(list(Distance = c(0.032, 0.034, 0.214, 0.263, 0.275, 
0.275, 0.45, 0.5, 0.5, 0.63, 0.8, 0.9, 0.9, 0.9, 0.9, 1, 1.1, 
1.1, 1.4, 1.7, 2, 2, 2, 2), Velocity = c(170L, 290L, -130L, -70L, 
-185L, -220L, 200L, 290L, 270L, -200L, 300L, -30L, 650L, 150L, 
500L, 920L, 450L, 500L, 500L, 960L, 500L, 850L, 800L, 1090L)), class = "data.frame", row.names = c(NA, 
-24L))
`./stars2.txt` <-
structure(list(Distance = c(1.6, 6.8, 8.3, 8.6, 9.4, 13.4, 21.1, 
35.1, 1.8, 10.2, 12, 12.5, 43, 41.2, 34, 75.3, 27.6, 69.9, 37.6, 
16.5, 22.2), Velocity = c(890L, 3810L, 4630L, 4820L, 5230L, 7500L, 
11800L, 19600L, 1000L, 5700L, 6700L, 7000L, 24000L, 23000L, 19000L, 
42000L, 15400L, 39000L, 21000L, 9200L, 12400L)), class = "data.frame", row.names = c(NA, 
-21L))
`./trout.txt` <-
structure(list(Sulfamerazine = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 15L, 15L, 15L, 15L, 15L, 
15L, 15L, 15L, 15L, 15L), Hemoglobin = c(6.7, 7.8, 5.5, 8.4, 
7, 7.8, 8.6, 7.4, 5.8, 7, 9.9, 8.4, 10.4, 9.3, 10.7, 11.9, 7.1, 
6.4, 8.6, 10.6, 10.4, 8.1, 10.6, 8.7, 10.7, 9.1, 8.8, 8.1, 7.8, 
8, 9.3, 9.3, 7.2, 7.8, 9.3, 10.2, 8.7, 8.6, 9.3, 7.2)), class = "data.frame", row.names = c(NA, 
-40L))
`./Waist.txt` <-
structure(list(Waist = c(74.75, 72.6, 81.8, 83.95, 74.65, 71.85, 
80.9, 83.4, 63.5, 73.2, 71.9, 75, 73.1, 79, 77, 68.85, 75.95, 
74.15, 73.8, 75.9, 76.85, 80.9, 79.9, 89.2, 82, 92, 86.6, 86, 
82.5, 83.5, 88.1, 90.8, 89.4, 102, 94.5, 91, 103, 80, 79, 83.5, 
76, 80.5, 86.5, 83, 107.1, 94.3, 94.5, 79.7, 79.3, 89.8, 83.8, 
85.2, 75.5, 78.4, 78.6, 87.8, 86.3, 85.5, 83.7, 77.6, 84.9, 79.8, 
108.3, 119.6, 119.9, 96.5, 105.5, 105, 107, 107, 101, 97, 100, 
108, 100, 103, 104, 106, 109, 103.5, 110, 110, 112, 108.5, 104, 
111, 108.5, 121, 109, 97.5, 105.5, 98, 94.5, 97, 105, 106, 99, 
91, 102.5, 106, 109.1, 115, 101, 100.1, 93.3, 101.8, 107.9, 108.5, 
80.5), AT = c(25.72, 25.89, 42.6, 42.8, 29.84, 21.68, 29.08, 
32.98, 11.44, 32.22, 28.32, 43.86, 38.21, 42.48, 30.96, 55.78, 
43.78, 33.41, 43.35, 29.31, 36.6, 40.25, 35.43, 60.09, 45.84, 
70.4, 83.45, 78.89, 64.75, 72.56, 89.31, 78.94, 83.55, 127, 121, 
107, 129, 74.02, 55.48, 73.13, 50.5, 50.88, 140, 96.54, 118, 
107, 123, 65.92, 81.29, 111, 90.73, 133, 41.9, 41.71, 58.16, 
88.85, 155, 70.77, 75.08, 57.05, 99.73, 27.96, 123, 90.41, 106, 
144, 121, 97.13, 166, 87.99, 154, 100, 123, 217, 140, 109, 127, 
112, 192, 132, 126, 153, 158, 183, 184, 121, 159, 245, 137, 165, 
152, 181, 80.95, 137, 125, 241, 134, 150, 198, 151, 229, 253, 
188, 124, 62.2, 133, 208, 208, 84.3)), class = "data.frame", row.names = c(NA, 
-109L))
`./Worldpop.txt` <-
structure(list(Year = 1981:2000, Pop.billion = c(4.533, 4.613, 
4.694, 4.774, 4.855, 4.938, 5.024, 5.11, 5.196, 5.284, 5.367, 
5.45, 5.531, 5.611, 5.691, 5.769, 5.847, 5.925, 6.003, 6.08)), class = "data.frame", row.names = c(NA, 
-20L))
`./Worldrecord.txt` <-
structure(list(Distance = c(100L, 200L, 400L, 800L, 1000L, 1500L, 
2000L, 3000L, 5000L, 10000L), MenRecord = c(9.58, 19.19, 43.03, 
100.91, 131.96, 206, 284.79, 440.67, 757.35, 1577.53), WomenRecord = c(10.49, 
21.34, 47.6, 113.28, 148.98, 230.07, 323.75, 486.11, 851.15, 
1757.45)), class = "data.frame", row.names = c(NA, -10L))
`./Wright.txt` <-
structure(list(Pressure = c(0L, 2L, 4L, 8L, 11L, 15L, 19L, 23L, 
27L, 34L, 38L, 37L, 29L, 27L, 0L, 5L, 11L, 17L, 22L, 27L, 31L, 
32L, 33L, 33L, 31L, 30L, 28L, 27L, 0L, 7L, 13L, 20L, 27L, 30L, 
32L, 33L, 33L, 32L, 32L, 32L, 32L, 32L, 7L, 11L, 15L, 18L, 22L, 
27L, 32L, 37L, 42L, 49L, 57L, 58L, 47L, 35L, 6L, 8L, 12L, 16L, 
19L, 24L, 28L, 33L, 39L, 47L, 54L, 55L, 40L, 33L, 5L, 8L, 11L, 
15L, 19L, 22L, 27L, 32L, 36L, 44L, 49L, 50L, 38L, 30L, 8L, 17L, 
25L, 31L, 38L, 52L, 61L, 63L, 60L, 50L, 46L, 45L, 43L, 41L, 8L, 
17L, 23L, 29L, 39L, 49L, 55L, 56L, 52L, 47L, 44L, 42L, 41L, 39L, 
8L, 15L, 22L, 27L, 39L, 46L, 50L, 51L, 48L, 44L, 41L, 40L, 40L, 
38L, 7L, 18L, 26L, 33L, 36L, 36L, 38L, 39L, 41L, 44L, 41L, 39L, 
39L, 38L, 7L, 16L, 25L, 32L, 37L, 37L, 38L, 41L, 42L, 41L, 39L, 
38L, 38L, 37L, 6L, 13L, 22L, 32L, 39L, 44L, 46L, 45L, 44L, 41L, 
39L, 38L, 38L, 36L, 8L, 15L, 22L, 27L, 29L, 30L, 32L, 34L, 35L, 
36L, 37L, 30L, 4L, 8L, 12L, 16L, 19L, 24L, 29L, 36L, 40L, 49L, 
56L, 52L, 38L, 30L, 4L, 6L, 10L, 14L, 19L, 22L, 28L, 33L, 37L, 
47L, 52L, 48L, 34L, 29L, 4L, 6L, 9L, 13L, 17L, 21L, 26L, 31L, 
35L, 44L, 49L, 45L, 32L, 29L), Angle = c(0, 2.5, 5, 7.5, 10, 
12.5, 15, 17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 
15, 17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 
17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 
20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 
25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 
30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 
35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 35, 
40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 35, 40, 
45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 35, 40, 45, 
0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 35, 40, 45, 0, 
2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 
5, 7.5, 10, 12.5, 15, 17.5, 20, 25, 30, 45, 0, 2.5, 5, 7.5, 10, 
12.5, 15, 17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 
15, 17.5, 20, 25, 30, 35, 40, 45, 0, 2.5, 5, 7.5, 10, 12.5, 15, 
17.5, 20, 25, 30, 35, 40, 45), Wing = c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 15L, 15L, 15L, 15L, 
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L)), class = "data.frame", row.names = c(NA, 
-222L))
.Random.seed <-
c(403L, 10L, -1416531451L, -1252007748L, -589248110L, 1181393549L, 
-670854969L, -428497490L, -1470484472L, 1061774347L, 1831543017L, 
-435265608L, -202442650L, 452159745L, -1642193005L, -2000195518L, 
-164644876L, -1643781641L, 791160301L, -2049677692L, -2079532886L, 
-404412907L, -1321403729L, 703574198L, 210759392L, 1940599331L, 
844717377L, 699031600L, -1472349618L, 683671225L, -138229045L, 
43780986L, 712489596L, 1807830719L, -1195837547L, -911577172L, 
1113173378L, -739806371L, -1619501481L, 342719806L, 876678520L, 
564633179L, -1232815687L, -339997688L, -344648010L, -1286003215L, 
880999459L, 1701287026L, -1897314620L, -793812857L, 483271773L, 
1172359764L, -1050730374L, 343679941L, 1199002911L, 1507947686L, 
794347056L, -1521247021L, 1652331249L, 106603040L, -1336884034L, 
807416009L, 2143842939L, -724477878L, 1109633196L, -1548365905L, 
-1260643483L, 1177317660L, 273906034L, -1184601619L, 1781136935L, 
-1370411442L, 783340200L, -1242271573L, 40507849L, 590378456L, 
2030666886L, -2042893983L, -1435816717L, 963679074L, -124609068L, 
1245550807L, 927558349L, -153306524L, 301297738L, -1958693451L, 
1244518671L, -1633188330L, -133873472L, 225465987L, -1628695903L, 
1977824400L, -740597906L, 1733703961L, -1648272981L, -281725030L, 
1667376988L, -791611809L, -1714158027L, -556620340L, -520674014L, 
1724321661L, 2099553399L, -465593954L, -1766125480L, 691801531L, 
-263314599L, -308391704L, 1026388246L, 1297093265L, 1864392515L, 
458308178L, -43037468L, 89478951L, 63624061L, 1788257908L, 10852442L, 
2063229093L, -816364865L, -775644858L, -813322288L, -1976555021L, 
-1457797871L, 657547584L, -1396059874L, -1979292183L, -745904357L, 
-1180462806L, 1782909516L, -1063725553L, 1744845125L, -1839848708L, 
-1687168686L, -1256001843L, -1597192569L, -533933714L, -614454456L, 
-272994485L, 1267676841L, -753792008L, -1576455386L, 1222079553L, 
-1011444269L, 2075236226L, -1682711628L, -679333065L, 2091635245L, 
-1251224764L, 557955178L, -1378983211L, 1823153263L, 389551478L, 
-1931567456L, 63445859L, -1358434303L, 1646271344L, -1287761138L, 
2083990905L, -737605365L, -2119960006L, -903040708L, 220470911L, 
1221101013L, -899154964L, 1379204418L, -338328931L, 1507471127L, 
1329942142L, 1260351032L, 369711387L, -1130692999L, -377963832L, 
-1435637002L, 559571761L, -1951550621L, -1140684494L, 2035612292L, 
-1335339321L, 443587997L, -859735788L, 2036111290L, -1435352571L, 
1414697951L, 1774086758L, -304912912L, -1368644845L, -408515407L, 
1111035744L, 1131777278L, 840043657L, 1085877179L, -1539209846L, 
930514028L, -1623646737L, -772139483L, -529714468L, -625416014L, 
604875693L, -1642401945L, -1684620146L, -975488664L, -1877907093L, 
-275027191L, 1692908952L, 1443933382L, 1710634529L, 646256307L, 
382155810L, 914507284L, -1487062377L, -1511263091L, -1213761116L, 
577463178L, 23646197L, 788381263L, -896349866L, 417428480L, 682687811L, 
1334669537L, 713165392L, 2067019438L, -2074901927L, 486582891L, 
-407822374L, 908615836L, -1004203361L, -112738059L, 611895692L, 
-1183751070L, -1176677638L, 167055184L, -571502548L, -1510633100L, 
-132060526L, 2089374304L, -1324319604L, -190567072L, 1688240354L, 
620517544L, -385563956L, -288471556L, -689940558L, 1957015536L, 
-75563580L, 1375832408L, 1973398906L, 597941680L, -1672488516L, 
723937876L, -1107874366L, -1065481440L, 937798588L, -732384176L, 
365385698L, -99017880L, -2063407284L, -506471684L, -747138318L, 
-377540352L, 758797428L, -1907361272L, -246701638L, 2043263440L, 
1199789036L, 1196988308L, -1068391214L, -574713760L, 1957427532L, 
-428925152L, -493542782L, 545452520L, -1882029076L, 1483980348L, 
941363826L, -406792336L, -2117123804L, 1578991160L, 897002906L, 
-996502064L, -1730940484L, -1555719532L, 54015618L, -1613268544L, 
499195708L, 1377781392L, 313738018L, -1430802936L, -522672372L, 
-456040548L, 1060435986L, 1785906048L, 1651818260L, 320284968L, 
-285329350L, -744101936L, 1748927084L, 1620853812L, 2139384978L, 
142554464L, 437559628L, 428581344L, 1078474658L, -1709351000L, 
2024721548L, 1184132028L, -805011342L, -1010265104L, -2060713916L, 
-1375644584L, 1591822394L, 666206320L, 1694927420L, 1472563988L, 
2067521218L, 863608544L, -1499659140L, -1806667568L, -1738660958L, 
-1227169240L, -1309500148L, -1024513092L, -1674015438L, 793347264L, 
720911924L, 1421928136L, -1259303238L, 1315276944L, -972854548L, 
-693050796L, 765388434L, 541399840L, -975578164L, -432851744L, 
-3704126L, 1890730024L, 1891115948L, -589819204L, 668786162L, 
-976146896L, -1595390044L, -676616776L, 1410991962L, -222771056L, 
50455420L, -1544594668L, -327384766L, 1848697600L, -690739268L, 
1637557072L, -1324683998L, -1295837624L, -1006196724L, 592775260L, 
-760000046L, 2043228672L, 147323220L, 1708950760L, 2068233466L, 
22830800L, -1359600340L, 1454754036L, -1013920366L, 830312800L, 
-1452158964L, 199128800L, 1436297826L, 546694824L, -669743540L, 
-1867160708L, -144186062L, -34933136L, -212300988L, 116818904L, 
735367034L, 1325238832L, 361491388L, 349950548L, 473400386L, 
-142770016L, -1100006724L, -613319216L, -1765849246L, -357217560L, 
-233057076L, -1081405956L, -900744718L, 507123328L, -900655628L, 
-1091587448L, 169647930L, 2001338192L, 1287650412L, 2001761684L, 
2135213138L, -1137436192L, 1350659276L, -1448925024L, -1995339390L, 
498194664L, -1535010068L, -579615428L, -1948793742L, 874777712L, 
1761842212L, 1545687096L, 730751770L, 1869374672L, 885855036L, 
1992105876L, 1629886338L, -841650752L, -579341764L, 1344960912L, 
-1043181022L, -2109272824L, 513958540L, -529725668L, 2115463314L, 
1934944640L, 427862548L, 264692520L, -1981587910L, 1684197840L, 
-1421101716L, -2071893068L, -1483469806L, 1055922656L, -718677044L, 
62654688L, -1406861278L, -336130776L, 2143104524L, -1902019780L, 
1376158706L, -553885968L, 213197380L, 748088920L, -210271430L, 
733536752L, 189623996L, -147182316L, 1027749570L, 21428320L, 
1475811196L, -1429292080L, 1889332514L, -261388632L, 1017551756L, 
758803644L, 284903218L, 1436170816L, 1500573876L, 1682496072L, 
-1406808646L, -621751792L, -326207764L, 51704723L, 146996469L, 
1077238994L, -318174432L, 22643465L, 553559099L, 1911892364L, 
-894910438L, -129274737L, 2072286169L, 294442094L, -1405519876L, 
278261101L, 772155159L, 163124960L, 716334270L, -712559989L, 
1344960781L, 1645538618L, 349531512L, 819619617L, -903544877L, 
-1328257292L, -1990625406L, -639459817L, -2019379999L, 2058670630L, 
-1730211036L, 485931989L, -880452737L, -1872994792L, -2003442378L, 
1195129795L, 1366270469L, -959907422L, 2013248912L, 73125177L, 
-1539667477L, -1338193188L, -203837686L, 570073599L, 895805513L, 
82477534L, 628189580L, -151124643L, -559880857L, 510506640L, 
1568299182L, -245753509L, -2042344131L, 935329706L, -933029816L, 
-1620610959L, -1429496349L, -1491937052L, 13530130L, -1474035737L, 
-271702095L, 1641724406L, -581204972L, -622593243L, 1700568111L, 
-1714319896L, 94874310L, 1376531315L, -213861419L, -1469201486L, 
1245894016L, -1781002903L, 1926357467L, -258684628L, 1239247674L, 
-1847130641L, -1471537031L, -1594258674L, 1985101532L, 1065618765L, 
-673783625L, 1202149952L, -932519138L, -1270896149L, 310289773L, 
-173929510L, 2035899800L, -1019509759L, 559609267L, 1102486740L, 
-402880030L, 1644921975L, -736388671L, 1289626438L, -1763840380L, 
13891637L, 553674783L, -1393979528L, 2037294678L, 60291811L, 
1868840101L, 1739793730L, -969002192L, -520775847L, 92355787L, 
1087671612L, -2052454038L, 565150623L, 636141097L, -1298472770L, 
-2139768404L, -1929009411L, -1208262073L, 668512560L, -1018807730L, 
-1102306693L, -186498595L, -1563654134L, -1112712920L, 574678929L, 
873097603L, 196085380L, 31077554L, 1379582983L, -337866671L, 
589873110L, 1092718260L, 1118449349L, 1129324559L, -717066104L, 
1814286758L, -330020525L, 1734048437L, 50909202L, 638984672L, 
900977737L, 1475183227L, 1963707212L, 284458714L, -1478946097L, 
98792089L, 1487937198L, -1517175876L, 673973293L, -47887401L, 
452157984L, 518939518L, -1658442421L, 979668813L, -1513167494L, 
1356453816L, -1863807647L, -1689009901L, 1534343476L, -733416638L, 
1683055447L, -1733631327L, 1279071078L, -868799132L, 144890005L, 
1247664575L, 2025819480L, -1054837898L, -1155395197L, 71848901L, 
-1894217502L, 660188496L, -1763378055L, -219508821L, -2052917988L, 
-1323957686L, 926025279L, -1854811851L)