S.STpiPS: Stratified Sampling Applying Without Replacement piPS Design...
In TeachingSampling: Selection of Samples and Parameter Estimation in Finite Population
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
Draws a probability proportional to size simple random sample without
replacement of size n_h in stratum h of size N_h
Usage
1
S.STpiPS(S,x,nh)
Arguments
S
Vector identifying the membership to the strata of each unit in the population
x
Vector of auxiliary information for each unit in the population
nh
Vector of sample size in each stratum
Details
The selected sample is drawn according to the Sunter method (sequential-list procedure) in each stratum
Value
The function returns a matrix of n=n_1+\cdots+n_h rows and two columns. Each element of the first column indicates the unit that
was selected. Each element of the second column indicates the inclusion probability of this unit
Author(s)
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
References
Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling. Springer.
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros.
Editorial Universidad Santo Tomas.
See Also
Examples
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############
## Example 1
############
# Vector U contains the label of a population of size N=5
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
# The auxiliary information
x <- c(52, 60, 75, 100, 50)
# Vector Strata contains an indicator variable of stratum membership
Strata <- c("A", "A", "A", "B", "B")
# Then sample size in each stratum
mh <- c(2,2)
# Draws a stratified PPS sample with replacement of size n=4
res <- S.STPPS(Strata, x, mh)
# The selected sample
sam <- res[,1]
U[sam]
# The selection probability of each unit selected to be in the sample
pk <- res[,2]
pk
############
## Example 2
############
# Uses the Lucy data to draw a stratified random sample
# according to a piPS design in each stratum
data(Lucy)
attach(Lucy)
# Level is the stratifying variable
summary(Level)
# Defines the size of each stratum
N1<-summary(Level)[[1]]
N2<-summary(Level)[[2]]
N3<-summary(Level)[[3]]
N1;N2;N3
# Defines the sample size at each stratum
n1<-70
n2<-100
n3<-200
nh<-c(n1,n2,n3)
nh
# Draws a stratified sample
S <- Level
x <- Employees
res <- S.STpiPS(S, x, nh)
sam<-res[,1]
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
data
dim(data)
# The selection probability of each unit selected in the sample
pik <- res[,2]
pik
Example output
Loading required package: dplyr
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Loading required package: magrittr
[1] "Ken" "Erik" "Sharon" "Sharon"
[1] 0.3208556 0.4010695 0.6666667 0.6666667
Big Medium Small
83 737 1576
[1] 83
[1] 737
[1] 1576
[1] 70 100 200
ID Ubication Level Zone Income Employees Taxes SPAM
1 AB001 c1k1 Small A 281 41 3.0 no
5 AB005 c1k5 Small A 391 91 7.0 yes
14 AB014 c1k14 Small A 330 23 4.0 yes
29 AB029 c1k29 Small A 310 94 4.0 yes
30 AB030 c1k30 Small A 354 33 5.0 yes
32 AB032 c1k32 Small A 380 18 6.0 yes
38 AB038 c1k38 Small A 462 84 9.0 yes
44 AB044 c1k44 Small A 337 44 5.0 no
59 AB062 c1k59 Small A 470 28 10.0 yes
61 AB064 c1k61 Small A 350 76 5.0 no
69 AB072 c1k69 Small A 390 95 7.0 yes
76 AB081 c1k76 Small A 313 82 4.0 no
77 AB082 c1k77 Small A 410 24 7.0 yes
80 AB085 c1k80 Small A 401 79 7.0 yes
95 AB1151 c1k95 Small A 490 98 10.5 yes
97 AB117 c1k97 Small A 378 30 6.0 no
99 AB1194 c1k99 Small B 480 49 10.0 no
100 AB121 c2k1 Small B 490 50 10.5 yes
127 AB1337 c2k28 Small B 270 32 3.0 no
128 AB1338 c2k29 Small B 282 69 3.0 yes
134 AB1343 c2k35 Small B 340 36 5.0 no
137 AB1346 c2k38 Small B 340 96 5.0 yes
143 AB1351 c2k44 Small B 245 39 2.0 no
144 AB1352 c2k45 Small B 273 16 3.0 yes
169 AB1375 c2k70 Small B 265 48 3.0 yes
177 AB1382 c2k78 Small B 319 55 4.0 yes
181 AB1386 c2k82 Small B 250 59 2.0 yes
188 AB1392 c2k89 Small B 313 14 4.0 no
190 AB1394 c2k91 Small B 296 69 3.0 no
191 AB1395 c2k92 Small B 339 48 5.0 no
197 AB1400 c2k98 Small B 220 50 2.0 no
198 AB1401 c2k99 Small B 201 81 1.0 yes
217 AB1419 c3k19 Small B 338 88 5.0 yes
227 AB1428 c3k29 Small B 300 33 3.0 yes
259 AB1457 c3k61 Small B 330 96 4.0 yes
263 AB1460 c3k65 Small B 300 78 3.0 yes
295 AB149 c3k97 Small B 118 70 0.5 no
302 AB1496 c4k5 Small B 202 73 1.0 no
304 AB1498 c4k7 Small B 360 53 5.0 yes
321 AB1513 c4k24 Small B 196 45 1.0 yes
323 AB1515 c4k26 Small B 241 87 2.0 yes
337 AB1528 c4k40 Small B 235 51 2.0 no
341 AB1531 c4k44 Small B 295 49 3.0 yes
351 AB1540 c4k54 Small B 300 82 3.0 no
356 AB1545 c4k59 Small B 235 71 2.0 no
358 AB1547 c4k61 Small B 258 68 2.0 yes
369 AB1557 c4k72 Small B 290 89 3.0 yes
386 AB1572 c4k89 Small B 270 76 3.0 no
394 AB158 c4k97 Small B 76 85 0.5 yes
395 AB1580 c4k98 Small B 299 85 3.0 no
399 AB1584 c5k3 Small B 230 18 2.0 yes
400 AB1585 c5k4 Small B 300 54 3.0 yes
405 AB159 c5k9 Small B 65 73 0.5 yes
410 AB1594 c5k14 Small B 264 44 3.0 no
421 AB1604 c5k25 Small B 315 27 4.0 yes
443 AB1624 c5k47 Small B 291 45 3.0 yes
456 AB1636 c5k60 Small B 251 23 2.0 no
467 AB1646 c5k71 Small B 334 76 5.0 no
471 AB165 c5k75 Small B 149 19 0.5 yes
478 AB1656 c5k82 Small B 233 35 2.0 no
487 AB1664 c5k91 Small B 273 56 3.0 yes
499 AB1675 c6k4 Small B 356 81 5.0 yes
503 AB1679 c6k8 Small B 250 59 2.0 yes
514 AB1689 c6k19 Small B 165 64 1.0 no
516 AB1690 c6k21 Small B 180 64 1.0 no
521 AB1695 c6k26 Small B 204 73 1.0 no
548 AB172 c6k53 Small B 80 77 0.5 yes
569 AB1739 c6k74 Small B 124 78 0.5 yes
574 AB1743 c6k79 Small B 196 89 1.0 yes
577 AB1746 c6k82 Small B 141 67 0.5 yes
586 AB1754 c6k91 Small B 145 59 0.5 yes
590 AB1758 c6k95 Small B 152 43 1.0 no
592 AB176 c6k97 Small B 83 85 0.5 yes
597 AB1764 c7k3 Small B 189 53 1.0 no
600 AB1767 c7k6 Small B 175 44 1.0 yes
612 AB1778 c7k18 Small B 134 31 0.5 yes
634 AB1798 c7k40 Small B 97 45 0.5 yes
636 AB180 c7k42 Small B 24 61 0.5 yes
639 AB1802 c7k45 Small B 131 82 0.5 no
642 AB1805 c7k48 Small B 154 87 1.0 yes
656 AB1818 c7k62 Small B 151 7 1.0 yes
666 AB1827 c7k72 Small B 160 56 1.0 yes
671 AB1831 c7k77 Small B 131 82 0.5 no
674 AB1834 c7k80 Small B 131 22 0.5 no
675 AB1835 c7k81 Small B 131 82 0.5 yes
712 AB1869 c8k19 Small C 172 56 1.0 yes
728 AB1883 c8k35 Small C 482 73 10.5 no
738 AB1892 c8k45 Small C 490 30 10.5 yes
739 AB1893 c8k46 Small C 391 71 7.0 yes
741 AB1895 c8k48 Small C 350 48 5.0 yes
756 AB1910 c8k63 Small C 350 92 5.0 yes
771 AB1924 c8k78 Small C 410 56 7.0 yes
786 AB194 c8k93 Small C 153 27 1.0 no
789 AB1944 c8k96 Small C 380 38 6.0 yes
809 AB1963 c9k17 Small C 400 95 7.0 no
811 AB1965 c9k19 Small C 475 89 10.0 yes
821 AB1974 c9k29 Small C 410 28 7.0 yes
823 AB1976 c9k31 Small C 440 70 8.0 yes
824 AB1977 c9k32 Small C 390 31 6.0 no
831 AB1983 c9k39 Small C 440 94 8.0 yes
836 AB1989 c9k44 Small C 350 92 5.0 no
845 AB1997 c9k53 Small C 400 95 7.0 yes
847 AB1999 c9k55 Small C 430 97 8.0 no
853 AB2005 c9k61 Small C 390 47 6.0 yes
854 AB2006 c9k62 Small C 330 87 4.0 yes
866 AB2022 c9k74 Small C 370 54 6.0 no
870 AB2026 c9k78 Small C 460 39 9.0 yes
890 AB2049 c9k98 Small C 480 85 10.0 yes
895 AB2055 c10k4 Small C 410 96 7.0 yes
898 AB2059 c10k7 Small C 417 20 7.0 no
912 AB2073 c10k21 Small C 420 76 8.0 no
915 AB2076 c10k24 Small C 421 101 8.0 no
924 AB2088 c10k33 Small C 482 37 10.5 no
937 AB2101 c10k46 Small C 400 39 7.0 yes
945 AB2110 c10k54 Small C 468 92 10.0 yes
949 AB2116 c10k58 Small C 457 95 9.0 no
957 AB2123 c10k66 Small C 376 30 6.0 yes
958 AB2124 c10k67 Small C 460 91 9.0 no
960 AB2128 c10k69 Small C 420 60 8.0 yes
962 AB213 c10k71 Small C 186 80 1.0 no
966 AB2133 c10k75 Small C 370 66 6.0 no
967 AB2134 c10k76 Small C 360 29 5.0 yes
979 AB2147 c10k88 Small C 487 105 10.5 yes
982 AB215 c10k91 Small C 180 36 1.0 yes
984 AB2151 c10k93 Small C 410 88 7.0 yes
985 AB2152 c10k94 Small C 452 63 9.0 no
999 AB2166 c11k9 Small C 392 75 7.0 yes
1000 AB2167 c11k10 Small C 449 70 9.0 no
1002 AB2169 c11k12 Small C 260 68 2.0 no
1006 AB2172 c11k16 Small C 370 54 6.0 yes
1008 AB2174 c11k18 Small C 490 74 10.5 yes
1018 AB2188 c11k28 Small C 386 23 6.0 yes
1026 AB2198 c11k36 Small C 366 69 6.0 no
1035 AB2207 c11k45 Small C 350 24 5.0 no
1038 AB221 c11k48 Small C 20 41 0.5 no
1040 AB2211 c11k50 Small C 360 41 5.0 yes
1045 AB2217 c11k55 Small C 430 69 8.0 no
1064 AB2237 c11k74 Small C 487 53 10.5 no
1075 AB2248 c11k85 Small C 411 52 7.0 yes
1078 AB2250 c11k88 Small C 435 73 8.0 no
1083 AB2258 c11k93 Small C 394 87 7.0 yes
1087 AB2261 c11k97 Small C 440 70 8.0 no
1090 AB2265 c12k1 Small C 477 61 10.0 yes
1094 AB227 c12k5 Small C 122 54 0.5 yes
1105 AB2280 c12k16 Small C 430 61 8.0 yes
1109 AB2285 c12k20 Small C 428 57 8.0 no
1118 AB2293 c12k29 Small C 450 79 9.0 yes
1126 AB2300 c12k37 Small C 450 27 9.0 no
1127 AB2301 c12k38 Small C 457 67 9.0 no
1143 AB2319 c12k54 Small C 419 100 7.0 yes
1146 AB2321 c12k57 Small C 454 51 9.0 yes
1156 AB2331 c12k67 Small C 248 79 2.0 yes
1157 AB2332 c12k68 Small C 434 61 8.0 no
1164 AB2341 c12k75 Small C 431 33 8.0 yes
1168 AB2345 c12k79 Small C 341 76 5.0 yes
1176 AB2353 c12k87 Small C 484 25 10.5 no
1181 AB2358 c12k92 Small C 348 56 5.0 yes
1186 AB2362 c12k97 Small C 382 66 6.0 yes
1197 AB2372 c13k9 Small C 467 84 10.0 no
1209 AB2387 c13k21 Small C 405 52 7.0 no
1265 AB286 c13k77 Small C 143 83 0.5 yes
1281 AB302 c13k93 Small C 204 53 1.0 yes
1288 AB309 c14k1 Small C 101 53 0.5 no
1299 AB320 c14k12 Small C 121 22 0.5 yes
1314 AB335 c14k27 Small C 65 65 0.5 yes
1329 AB350 c14k42 Small C 139 79 0.5 yes
1339 AB360 c14k52 Small C 167 72 1.0 yes
1351 AB372 c14k64 Small C 154 55 1.0 yes
1379 AB400 c14k92 Small C 146 35 0.5 yes
1390 AB411 c15k4 Small C 168 32 1.0 yes
1391 AB412 c15k5 Small C 76 85 0.5 yes
1393 AB414 c15k7 Small C 113 62 0.5 no
1395 AB416 c15k9 Small C 174 36 1.0 no
1402 AB423 c15k16 Small C 300 50 3.0 yes
1409 AB430 c15k23 Small C 276 48 3.0 yes
1412 AB433 c15k26 Small C 232 87 2.0 no
1460 AB481 c15k74 Small C 227 50 2.0 no
1465 AB486 c15k79 Small C 342 40 5.0 no
1467 AB488 c15k81 Small C 195 61 1.0 no
1475 AB496 c15k89 Small C 235 87 2.0 yes
1476 AB497 c15k90 Small C 239 31 2.0 yes
1481 AB502 c15k95 Small C 268 52 3.0 no
1491 AB512 c16k6 Small C 250 75 2.0 yes
1494 AB515 c16k9 Small C 274 44 3.0 no
1500 AB521 c16k15 Small C 270 76 3.0 no
1507 AB528 c16k22 Small C 214 34 1.0 no
1514 AB535 c16k29 Small C 286 41 3.0 yes
1519 AB540 c16k34 Small C 283 65 3.0 no
1522 AB543 c16k37 Small C 318 71 4.0 yes
1526 AB547 c16k41 Small C 202 45 1.0 yes
1532 AB553 c16k47 Small C 308 14 4.0 no
1539 AB560 c16k54 Small C 243 75 2.0 yes
1545 AB566 c16k60 Small C 200 69 1.0 yes
1553 AB623 c16k68 Small D 486 97 10.5 yes
1555 AB640 c16k70 Small D 370 38 6.0 yes
1558 AB661 c16k73 Small D 460 96 9.0 no
1564 AB730 c16k79 Small D 420 101 8.0 yes
1566 AB754 c16k81 Small D 474 97 10.0 no
1573 AB852 c16k88 Small E 480 89 10.0 yes
1575 AB958 c16k90 Small E 490 38 10.5 yes
1584 AB093 c16k99 Medium A 651 42 22.0 no
1590 AB1002 c17k6 Medium A 743 127 27.0 no
1595 AB1007 c17k11 Medium A 740 122 27.0 no
1596 AB1009 c17k12 Medium A 600 44 17.0 yes
1602 AB1015 c17k18 Medium A 834 140 35.0 yes
1616 AB1030 c17k32 Medium A 710 92 26.0 yes
1622 AB1036 c17k38 Medium A 904 77 41.0 yes
1637 AB1055 c17k53 Medium A 550 87 14.0 yes
1652 AB107 c17k68 Medium A 560 72 15.0 yes
1653 AB1070 c17k69 Medium A 820 106 34.0 yes
1657 AB1075 c17k73 Medium A 563 64 15.0 no
1659 AB1077 c17k75 Medium A 611 102 19.0 yes
1661 AB1079 c17k77 Medium A 557 32 14.0 yes
1693 AB1113 c18k10 Medium A 530 61 13.0 yes
1706 AB1134 c18k23 Medium A 619 78 19.0 no
1718 AB1146 c18k35 Medium A 760 84 29.0 no
1719 AB1147 c18k36 Medium A 960 73 44.0 yes
1722 AB1150 c18k39 Medium A 512 92 12.0 no
1723 AB1152 c18k40 Medium A 560 60 15.0 no
1734 AB1164 c18k51 Medium A 753 56 29.0 yes
1737 AB1167 c18k54 Medium A 850 125 36.0 yes
1750 AB1181 c18k67 Medium A 810 120 32.0 no
1755 AB1186 c18k72 Medium A 990 145 47.0 no
1759 AB1190 c18k76 Medium B 556 52 14.0 yes
1765 AB1198 c18k82 Medium B 958 149 44.0 no
1766 AB120 c18k83 Medium B 600 48 18.0 no
1773 AB1207 c18k90 Medium B 920 118 41.0 yes
1776 AB1213 c18k93 Medium B 530 105 13.0 yes
1779 AB1216 c18k96 Medium B 632 112 20.0 no
1793 AB1239 c19k11 Medium B 550 95 14.0 no
1796 AB1243 c19k14 Medium B 540 74 13.0 yes
1807 AB1256 c19k25 Medium B 618 70 19.0 yes
1824 AB1273 c19k42 Medium B 621 43 19.0 yes
1829 AB1278 c19k47 Medium B 804 103 32.0 no
1831 AB1280 c19k49 Medium B 963 106 45.0 yes
1835 AB1285 c19k53 Medium B 669 79 22.0 yes
1845 AB1296 c19k63 Medium B 674 47 23.0 yes
1847 AB1298 c19k65 Medium B 619 46 19.0 yes
1851 AB1302 c19k69 Medium B 944 131 43.0 no
1852 AB1303 c19k70 Medium B 503 91 12.0 yes
1862 AB1315 c19k80 Medium B 915 129 41.0 yes
1863 AB1316 c19k81 Medium B 649 117 21.0 no
1864 AB1318 c19k82 Medium B 511 104 12.0 yes
1867 AB1321 c19k85 Medium B 619 94 19.0 yes
1873 AB1327 c19k91 Medium B 500 42 11.0 yes
1877 AB1331 c19k95 Medium B 960 78 45.0 yes
1883 AB1942 c20k2 Medium C 560 84 14.0 yes
1894 AB2031 c20k13 Medium C 540 74 13.0 no
1920 AB2179 c20k39 Medium C 579 49 16.0 yes
1929 AB2227 c20k48 Medium C 512 92 12.0 no
1931 AB2238 c20k50 Medium C 540 66 13.0 no
1948 AB2378 c20k67 Medium C 510 48 12.0 yes
1950 AB2382 c20k69 Medium C 553 96 14.0 yes
1962 AB580 c20k81 Medium C 550 67 14.0 yes
1967 AB585 c20k86 Medium C 620 79 19.0 no
1969 AB587 c20k88 Medium C 660 118 22.0 no
1971 AB589 c20k90 Medium C 580 70 16.0 yes
1977 AB597 c20k96 Medium C 570 73 15.0 yes
1988 AB611 c22k8 Medium C 640 69 21.0 no
1990 AB613 c22k10 Medium D 725 89 27.0 yes
2039 AB672 c22k59 Medium D 500 99 11.0 no
2047 AB682 c22k67 Medium D 650 81 22.0 yes
2048 AB683 c22k68 Medium D 656 90 22.0 no
2055 AB690 c22k75 Medium D 750 95 28.0 yes
2074 AB710 c22k94 Medium D 630 75 20.0 yes
2077 AB713 c22k97 Medium D 590 55 16.0 yes
2083 AB719 c23k4 Medium D 630 103 19.0 yes
2084 AB720 c23k5 Medium D 730 129 27.0 yes
2124 AB777 c23k45 Medium D 580 54 16.0 yes
2136 AB789 c23k57 Medium D 790 102 31.0 yes
2145 AB798 c23k66 Medium D 880 120 38.0 no
2147 AB803 c23k68 Medium D 700 66 25.0 yes
2152 AB808 c23k73 Medium D 986 151 46.0 yes
2164 AB821 c23k85 Medium D 674 92 23.0 yes
2166 AB823 c23k87 Medium D 692 93 24.0 yes
2167 AB824 c23k88 Medium D 683 96 23.0 no
2171 AB829 c23k92 Medium D 595 87 17.0 yes
2177 AB836 c23k98 Medium E 590 79 17.0 no
2181 AB840 c24k3 Medium E 694 73 24.0 yes
2196 AB856 c24k18 Medium E 810 113 32.0 no
2199 AB859 c24k21 Medium E 810 105 33.0 yes
2201 AB861 c24k23 Medium E 870 135 38.0 yes
2212 AB875 c24k34 Medium E 850 141 36.0 yes
2228 AB896 c24k50 Medium E 620 98 19.0 yes
2230 AB898 c24k52 Medium E 670 115 23.0 yes
2235 AB903 c24k57 Medium E 850 114 36.0 yes
2252 AB926 c24k74 Medium E 640 100 20.0 yes
2258 AB933 c24k80 Medium E 550 87 14.0 yes
2263 AB938 c24k85 Medium E 520 52 12.0 no
2267 AB942 c24k89 Medium E 610 86 18.0 no
2268 AB943 c24k90 Medium E 610 73 18.0 yes
2269 AB944 c24k91 Medium E 670 95 23.0 yes
2274 AB949 c24k96 Medium E 644 53 21.0 yes
2290 AB970 c25k13 Medium E 809 123 32.0 no
2291 AB971 c25k14 Medium E 735 110 27.0 yes
2299 AB979 c25k22 Medium E 960 138 45.0 yes
2303 AB989 c25k26 Medium E 852 142 36.0 no
2309 AB995 c25k32 Medium E 550 51 14.0 no
2310 AB996 c25k33 Medium E 581 102 16.0 yes
2311 AB997 c25k34 Medium E 590 75 16.0 no
2315 AB098 c25k38 Big A 1155 117 62.0 yes
2316 AB1008 c25k39 Big A 1390 171 77.0 yes
2318 AB1028 c25k41 Big A 1193 122 63.0 yes
2319 AB1029 c25k42 Big A 1110 97 58.0 yes
2323 AB1041 c25k46 Big A 1100 109 58.0 yes
2324 AB1042 c25k47 Big A 1100 161 57.0 yes
2325 AB1072 c25k48 Big A 1434 157 83.0 yes
2326 AB1084 c25k49 Big A 1396 172 82.0 no
2327 AB1093 c25k50 Big A 1063 146 54.0 yes
2328 AB1094 c25k51 Big A 1153 144 62.0 yes
2329 AB1096 c25k52 Big A 1620 232 152.0 no
2330 AB1108 c25k53 Big A 1094 83 57.0 yes
2331 AB1116 c25k54 Big A 1090 137 55.0 yes
2332 AB1117 c25k55 Big A 1315 170 70.0 yes
2333 AB1123 c25k56 Big A 1020 133 50.0 yes
2334 AB1124 c25k57 Big A 1130 126 59.0 yes
2335 AB1125 c25k58 Big A 1450 133 94.0 yes
2336 AB1126 c25k59 Big A 1614 159 138.0 yes
2337 AB1130 c25k60 Big A 1080 140 54.0 yes
2338 AB1132 c25k61 Big A 2510 258 305.0 yes
2339 AB1148 c25k62 Big A 1230 140 64.0 yes
2340 AB1153 c25k63 Big A 1121 146 59.0 yes
2341 AB1172 c25k64 Big A 1440 133 84.0 yes
2343 AB1187 c25k66 Big A 1459 176 99.0 no
2347 AB1211 c25k70 Big B 1050 142 52.0 yes
2348 AB1212 c25k71 Big B 1616 158 142.0 yes
2349 AB1217 c25k72 Big B 1101 117 58.0 yes
2350 AB1220 c25k73 Big B 1480 193 104.0 no
2351 AB1231 c25k74 Big B 1160 121 62.0 no
2352 AB1232 c25k75 Big B 1490 201 105.0 yes
2353 AB1251 c25k76 Big B 1003 147 49.0 yes
2354 AB1283 c25k77 Big B 1510 163 107.0 yes
2355 AB1308 c25k78 Big B 1170 158 63.0 no
2356 AB1317 c25k79 Big B 1030 122 51.0 no
2357 AB590 c25k80 Big C 1360 134 76.0 yes
2358 AB636 c25k81 Big D 1024 149 50.0 yes
2359 AB637 c25k82 Big D 1405 111 83.0 yes
2360 AB670 c25k83 Big D 1600 189 112.0 yes
2361 AB725 c25k84 Big D 1005 83 49.0 yes
2362 AB727 c25k85 Big D 1450 162 94.0 yes
2363 AB741 c25k86 Big D 1093 119 56.0 no
2364 AB742 c25k87 Big D 1030 149 50.0 yes
2365 AB744 c25k88 Big D 1370 182 77.0 no
2367 AB746 c25k90 Big D 1090 105 55.0 yes
2368 AB747 c25k91 Big D 1280 145 65.0 yes
2369 AB748 c25k92 Big D 1300 172 68.0 yes
2370 AB749 c25k93 Big D 1911 263 196.0 yes
2372 AB767 c25k95 Big D 1300 176 68.0 yes
2373 AB799 c25k96 Big D 1094 131 56.0 no
2374 AB862 c25k97 Big E 1010 132 50.0 yes
2375 AB863 c25k98 Big E 1565 162 109.0 no
2376 AB864 c25k99 Big E 1360 126 73.0 yes
2378 AB891 c26k2 Big E 1040 118 52.0 no
2379 AB892 c26k3 Big E 1084 92 54.0 yes
2380 AB893 c26k4 Big E 1551 168 107.0 no
2381 AB904 c26k5 Big E 1035 86 51.0 yes
2382 AB905 c26k6 Big E 1405 110 83.0 no
2383 AB906 c26k7 Big E 1250 100 64.0 yes
2384 AB908 c26k8 Big E 1305 150 70.0 yes
2385 AB912 c26k9 Big E 1088 133 55.0 no
2386 AB916 c26k10 Big E 1161 157 62.0 no
2387 AB932 c26k11 Big E 1360 104 72.0 yes
2388 AB953 c26k12 Big E 1085 116 54.0 no
2389 AB956 c26k13 Big E 1040 78 51.0 yes
2390 AB957 c26k14 Big E 1220 163 63.0 no
2391 AB983 c26k15 Big E 1030 145 51.0 yes
2392 AB984 c26k16 Big E 1020 89 50.0 yes
2394 AB986 c26k18 Big E 1297 161 67.0 no
2395 AB987 c26k19 Big E 1640 225 169.0 yes
2396 AB988 c26k20 Big E 1860 253 176.0 yes
[1] 370 8
[1] 0.10142741 0.22511936 0.05689830 0.23254088 0.08163669 0.04452910
[7] 0.20780249 0.10884892 0.06926750 0.18801178 0.23501472 0.20285481
[13] 0.05937214 0.19543329 0.24243624 0.07421517 0.12121812 0.12369196
[19] 0.07916285 0.17069490 0.08905821 0.23748856 0.09647973 0.03958143
[25] 0.11874428 0.13606115 0.14595651 0.03463375 0.17069490 0.11874428
[31] 0.12369196 0.20038097 0.21769785 0.08163669 0.23748856 0.19295945
[37] 0.17316874 0.18059026 0.13111348 0.11132276 0.21522401 0.12616580
[43] 0.12121812 0.20285481 0.17564258 0.16822106 0.22017168 0.18801178
[49] 0.21027633 0.21027633 0.04452910 0.13358731 0.18059026 0.10884892
[55] 0.06679366 0.11132276 0.05689830 0.18801178 0.04700294 0.08658437
[61] 0.13853499 0.20038097 0.14595651 0.15832571 0.15832571 0.18059026
[67] 0.19048561 0.19295945 0.22017168 0.16574722 0.14595651 0.10637508
[73] 0.21027633 0.13111348 0.10884892 0.07668901 0.11132276 0.15090419
[79] 0.20285481 0.21522401 0.01731687 0.13853499 0.20285481 0.05442446
[85] 0.20285481 0.13853499 0.18059026 0.07421517 0.17564258 0.11874428
[91] 0.22759320 0.13853499 0.06679366 0.09400589 0.23501472 0.22017168
[97] 0.06926750 0.17316874 0.07668901 0.23254088 0.22759320 0.23501472
[103] 0.23996240 0.11627044 0.21522401 0.13358731 0.09647973 0.21027633
[109] 0.23748856 0.04947678 0.18801178 0.24985775 0.09153205 0.09647973
[115] 0.22759320 0.23501472 0.07421517 0.22511936 0.14843035 0.19790713
[121] 0.16327338 0.07174134 0.25975311 0.08905821 0.21769785 0.15585187
[127] 0.18553794 0.17316874 0.16822106 0.13358731 0.18306410 0.05689830
[133] 0.17069490 0.05937214 0.10142741 0.10142741 0.17069490 0.13111348
[139] 0.12863964 0.18059026 0.21522401 0.17316874 0.15090419 0.13358731
[145] 0.15090419 0.14100883 0.19543329 0.06679366 0.16574722 0.24738392
[151] 0.12616580 0.19543329 0.15090419 0.08163669 0.18801178 0.06184598
[157] 0.13853499 0.16327338 0.20780249 0.12863964 0.20532865 0.13111348
[163] 0.13111348 0.05442446 0.16079954 0.19543329 0.17811642 0.13606115
[169] 0.08658437 0.07916285 0.21027633 0.15337803 0.08905821 0.12369196
[175] 0.11874428 0.21522401 0.12369196 0.09895357 0.15090419 0.21522401
[181] 0.07668901 0.12863964 0.18553794 0.10884892 0.18801178 0.08411053
[187] 0.10142741 0.16079954 0.17564258 0.11132276 0.03463375 0.18553794
[193] 0.17069490 0.23996240 0.09400589 0.23748856 0.24985775 0.23996240
[199] 0.22017168 0.09400589 0.07041899 0.21293362 0.20455041 0.07377228
[205] 0.23472998 0.15425113 0.12910149 0.14586791 0.12071827 0.17772413
[211] 0.10730513 0.17101755 0.05365257 0.10227520 0.13077813 0.14083799
[217] 0.12239492 0.15425113 0.10059856 0.09389199 0.20958034 0.20119712
[223] 0.24311319 0.08718542 0.24981976 0.08047885 0.19784384 0.17604748
[229] 0.18778398 0.15928106 0.12407156 0.11736499 0.07209564 0.17269420
[235] 0.17772413 0.13245477 0.07880221 0.07712556 0.21964019 0.15257448
[241] 0.21628691 0.19616719 0.17437084 0.15760441 0.07041899 0.13077813
[247] 0.14083799 0.12407156 0.08215549 0.15425113 0.11065842 0.08047885
[253] 0.16095770 0.11233506 0.13245477 0.19784384 0.11736499 0.12239492
[259] 0.11568835 0.14922120 0.16598763 0.13580806 0.15089784 0.15928106
[265] 0.12574820 0.09221535 0.17269420 0.21628691 0.09053871 0.17101755
[271] 0.20119712 0.11065842 0.25317305 0.15425113 0.15592777 0.16095770
[277] 0.14586791 0.13245477 0.12239492 0.18946062 0.17604748 0.22634676
[283] 0.23640662 0.16431098 0.19281391 0.19113727 0.16766427 0.14586791
[289] 0.08718542 0.14419127 0.12239492 0.15928106 0.08886206 0.20622705
[295] 0.18443070 0.23137669 0.23808326 0.08550878 0.17101755 0.12574820
[301] 0.77411910 1.00000000 0.80720111 0.64179104 0.72118788 1.00000000
[307] 1.00000000 1.00000000 0.96599477 0.95276196 1.00000000 0.54916141
[313] 0.90644715 1.00000000 0.87998154 0.83366672 0.87998154 1.00000000
[319] 0.92629635 1.00000000 0.92629635 0.96599477 0.87998154 1.00000000
[325] 0.93952916 1.00000000 0.77411910 1.00000000 0.80058471 1.00000000
[331] 0.97261117 1.00000000 1.00000000 0.80720111 0.88659794 0.98584398
[337] 0.73442068 1.00000000 0.54916141 1.00000000 0.78735190 0.98584398
[343] 1.00000000 0.69472226 0.95937837 1.00000000 1.00000000 1.00000000
[349] 0.86674873 0.87336513 1.00000000 0.83366672 0.78073550 0.60870903
[355] 1.00000000 0.56901062 0.72780428 0.66164025 0.99246038 0.87998154
[361] 1.00000000 0.68810586 0.76750269 0.51607940 1.00000000 0.95937837
[367] 0.58885982 1.00000000 1.00000000 1.00000000
TeachingSampling documentation built on April 22, 2020, 1:05 a.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
Draws a probability proportional to size simple random sample without replacement of size n_h in stratum h of size N_h
Usage
1 | S.STpiPS(S,x,nh)
|
Arguments
S |
Vector identifying the membership to the strata of each unit in the population |
x |
Vector of auxiliary information for each unit in the population |
nh |
Vector of sample size in each stratum |
Details
The selected sample is drawn according to the Sunter method (sequential-list procedure) in each stratum
Value
The function returns a matrix of n=n_1+\cdots+n_h rows and two columns. Each element of the first column indicates the unit that was selected. Each element of the second column indicates the inclusion probability of this unit
Author(s)
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
References
Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling. Springer.
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros.
Editorial Universidad Santo Tomas.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 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 | ############
## Example 1
############
# Vector U contains the label of a population of size N=5
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
# The auxiliary information
x <- c(52, 60, 75, 100, 50)
# Vector Strata contains an indicator variable of stratum membership
Strata <- c("A", "A", "A", "B", "B")
# Then sample size in each stratum
mh <- c(2,2)
# Draws a stratified PPS sample with replacement of size n=4
res <- S.STPPS(Strata, x, mh)
# The selected sample
sam <- res[,1]
U[sam]
# The selection probability of each unit selected to be in the sample
pk <- res[,2]
pk
############
## Example 2
############
# Uses the Lucy data to draw a stratified random sample
# according to a piPS design in each stratum
data(Lucy)
attach(Lucy)
# Level is the stratifying variable
summary(Level)
# Defines the size of each stratum
N1<-summary(Level)[[1]]
N2<-summary(Level)[[2]]
N3<-summary(Level)[[3]]
N1;N2;N3
# Defines the sample size at each stratum
n1<-70
n2<-100
n3<-200
nh<-c(n1,n2,n3)
nh
# Draws a stratified sample
S <- Level
x <- Employees
res <- S.STpiPS(S, x, nh)
sam<-res[,1]
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
data
dim(data)
# The selection probability of each unit selected in the sample
pik <- res[,2]
pik
|
Example output
Loading required package: dplyr
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Loading required package: magrittr
[1] "Ken" "Erik" "Sharon" "Sharon"
[1] 0.3208556 0.4010695 0.6666667 0.6666667
Big Medium Small
83 737 1576
[1] 83
[1] 737
[1] 1576
[1] 70 100 200
ID Ubication Level Zone Income Employees Taxes SPAM
1 AB001 c1k1 Small A 281 41 3.0 no
5 AB005 c1k5 Small A 391 91 7.0 yes
14 AB014 c1k14 Small A 330 23 4.0 yes
29 AB029 c1k29 Small A 310 94 4.0 yes
30 AB030 c1k30 Small A 354 33 5.0 yes
32 AB032 c1k32 Small A 380 18 6.0 yes
38 AB038 c1k38 Small A 462 84 9.0 yes
44 AB044 c1k44 Small A 337 44 5.0 no
59 AB062 c1k59 Small A 470 28 10.0 yes
61 AB064 c1k61 Small A 350 76 5.0 no
69 AB072 c1k69 Small A 390 95 7.0 yes
76 AB081 c1k76 Small A 313 82 4.0 no
77 AB082 c1k77 Small A 410 24 7.0 yes
80 AB085 c1k80 Small A 401 79 7.0 yes
95 AB1151 c1k95 Small A 490 98 10.5 yes
97 AB117 c1k97 Small A 378 30 6.0 no
99 AB1194 c1k99 Small B 480 49 10.0 no
100 AB121 c2k1 Small B 490 50 10.5 yes
127 AB1337 c2k28 Small B 270 32 3.0 no
128 AB1338 c2k29 Small B 282 69 3.0 yes
134 AB1343 c2k35 Small B 340 36 5.0 no
137 AB1346 c2k38 Small B 340 96 5.0 yes
143 AB1351 c2k44 Small B 245 39 2.0 no
144 AB1352 c2k45 Small B 273 16 3.0 yes
169 AB1375 c2k70 Small B 265 48 3.0 yes
177 AB1382 c2k78 Small B 319 55 4.0 yes
181 AB1386 c2k82 Small B 250 59 2.0 yes
188 AB1392 c2k89 Small B 313 14 4.0 no
190 AB1394 c2k91 Small B 296 69 3.0 no
191 AB1395 c2k92 Small B 339 48 5.0 no
197 AB1400 c2k98 Small B 220 50 2.0 no
198 AB1401 c2k99 Small B 201 81 1.0 yes
217 AB1419 c3k19 Small B 338 88 5.0 yes
227 AB1428 c3k29 Small B 300 33 3.0 yes
259 AB1457 c3k61 Small B 330 96 4.0 yes
263 AB1460 c3k65 Small B 300 78 3.0 yes
295 AB149 c3k97 Small B 118 70 0.5 no
302 AB1496 c4k5 Small B 202 73 1.0 no
304 AB1498 c4k7 Small B 360 53 5.0 yes
321 AB1513 c4k24 Small B 196 45 1.0 yes
323 AB1515 c4k26 Small B 241 87 2.0 yes
337 AB1528 c4k40 Small B 235 51 2.0 no
341 AB1531 c4k44 Small B 295 49 3.0 yes
351 AB1540 c4k54 Small B 300 82 3.0 no
356 AB1545 c4k59 Small B 235 71 2.0 no
358 AB1547 c4k61 Small B 258 68 2.0 yes
369 AB1557 c4k72 Small B 290 89 3.0 yes
386 AB1572 c4k89 Small B 270 76 3.0 no
394 AB158 c4k97 Small B 76 85 0.5 yes
395 AB1580 c4k98 Small B 299 85 3.0 no
399 AB1584 c5k3 Small B 230 18 2.0 yes
400 AB1585 c5k4 Small B 300 54 3.0 yes
405 AB159 c5k9 Small B 65 73 0.5 yes
410 AB1594 c5k14 Small B 264 44 3.0 no
421 AB1604 c5k25 Small B 315 27 4.0 yes
443 AB1624 c5k47 Small B 291 45 3.0 yes
456 AB1636 c5k60 Small B 251 23 2.0 no
467 AB1646 c5k71 Small B 334 76 5.0 no
471 AB165 c5k75 Small B 149 19 0.5 yes
478 AB1656 c5k82 Small B 233 35 2.0 no
487 AB1664 c5k91 Small B 273 56 3.0 yes
499 AB1675 c6k4 Small B 356 81 5.0 yes
503 AB1679 c6k8 Small B 250 59 2.0 yes
514 AB1689 c6k19 Small B 165 64 1.0 no
516 AB1690 c6k21 Small B 180 64 1.0 no
521 AB1695 c6k26 Small B 204 73 1.0 no
548 AB172 c6k53 Small B 80 77 0.5 yes
569 AB1739 c6k74 Small B 124 78 0.5 yes
574 AB1743 c6k79 Small B 196 89 1.0 yes
577 AB1746 c6k82 Small B 141 67 0.5 yes
586 AB1754 c6k91 Small B 145 59 0.5 yes
590 AB1758 c6k95 Small B 152 43 1.0 no
592 AB176 c6k97 Small B 83 85 0.5 yes
597 AB1764 c7k3 Small B 189 53 1.0 no
600 AB1767 c7k6 Small B 175 44 1.0 yes
612 AB1778 c7k18 Small B 134 31 0.5 yes
634 AB1798 c7k40 Small B 97 45 0.5 yes
636 AB180 c7k42 Small B 24 61 0.5 yes
639 AB1802 c7k45 Small B 131 82 0.5 no
642 AB1805 c7k48 Small B 154 87 1.0 yes
656 AB1818 c7k62 Small B 151 7 1.0 yes
666 AB1827 c7k72 Small B 160 56 1.0 yes
671 AB1831 c7k77 Small B 131 82 0.5 no
674 AB1834 c7k80 Small B 131 22 0.5 no
675 AB1835 c7k81 Small B 131 82 0.5 yes
712 AB1869 c8k19 Small C 172 56 1.0 yes
728 AB1883 c8k35 Small C 482 73 10.5 no
738 AB1892 c8k45 Small C 490 30 10.5 yes
739 AB1893 c8k46 Small C 391 71 7.0 yes
741 AB1895 c8k48 Small C 350 48 5.0 yes
756 AB1910 c8k63 Small C 350 92 5.0 yes
771 AB1924 c8k78 Small C 410 56 7.0 yes
786 AB194 c8k93 Small C 153 27 1.0 no
789 AB1944 c8k96 Small C 380 38 6.0 yes
809 AB1963 c9k17 Small C 400 95 7.0 no
811 AB1965 c9k19 Small C 475 89 10.0 yes
821 AB1974 c9k29 Small C 410 28 7.0 yes
823 AB1976 c9k31 Small C 440 70 8.0 yes
824 AB1977 c9k32 Small C 390 31 6.0 no
831 AB1983 c9k39 Small C 440 94 8.0 yes
836 AB1989 c9k44 Small C 350 92 5.0 no
845 AB1997 c9k53 Small C 400 95 7.0 yes
847 AB1999 c9k55 Small C 430 97 8.0 no
853 AB2005 c9k61 Small C 390 47 6.0 yes
854 AB2006 c9k62 Small C 330 87 4.0 yes
866 AB2022 c9k74 Small C 370 54 6.0 no
870 AB2026 c9k78 Small C 460 39 9.0 yes
890 AB2049 c9k98 Small C 480 85 10.0 yes
895 AB2055 c10k4 Small C 410 96 7.0 yes
898 AB2059 c10k7 Small C 417 20 7.0 no
912 AB2073 c10k21 Small C 420 76 8.0 no
915 AB2076 c10k24 Small C 421 101 8.0 no
924 AB2088 c10k33 Small C 482 37 10.5 no
937 AB2101 c10k46 Small C 400 39 7.0 yes
945 AB2110 c10k54 Small C 468 92 10.0 yes
949 AB2116 c10k58 Small C 457 95 9.0 no
957 AB2123 c10k66 Small C 376 30 6.0 yes
958 AB2124 c10k67 Small C 460 91 9.0 no
960 AB2128 c10k69 Small C 420 60 8.0 yes
962 AB213 c10k71 Small C 186 80 1.0 no
966 AB2133 c10k75 Small C 370 66 6.0 no
967 AB2134 c10k76 Small C 360 29 5.0 yes
979 AB2147 c10k88 Small C 487 105 10.5 yes
982 AB215 c10k91 Small C 180 36 1.0 yes
984 AB2151 c10k93 Small C 410 88 7.0 yes
985 AB2152 c10k94 Small C 452 63 9.0 no
999 AB2166 c11k9 Small C 392 75 7.0 yes
1000 AB2167 c11k10 Small C 449 70 9.0 no
1002 AB2169 c11k12 Small C 260 68 2.0 no
1006 AB2172 c11k16 Small C 370 54 6.0 yes
1008 AB2174 c11k18 Small C 490 74 10.5 yes
1018 AB2188 c11k28 Small C 386 23 6.0 yes
1026 AB2198 c11k36 Small C 366 69 6.0 no
1035 AB2207 c11k45 Small C 350 24 5.0 no
1038 AB221 c11k48 Small C 20 41 0.5 no
1040 AB2211 c11k50 Small C 360 41 5.0 yes
1045 AB2217 c11k55 Small C 430 69 8.0 no
1064 AB2237 c11k74 Small C 487 53 10.5 no
1075 AB2248 c11k85 Small C 411 52 7.0 yes
1078 AB2250 c11k88 Small C 435 73 8.0 no
1083 AB2258 c11k93 Small C 394 87 7.0 yes
1087 AB2261 c11k97 Small C 440 70 8.0 no
1090 AB2265 c12k1 Small C 477 61 10.0 yes
1094 AB227 c12k5 Small C 122 54 0.5 yes
1105 AB2280 c12k16 Small C 430 61 8.0 yes
1109 AB2285 c12k20 Small C 428 57 8.0 no
1118 AB2293 c12k29 Small C 450 79 9.0 yes
1126 AB2300 c12k37 Small C 450 27 9.0 no
1127 AB2301 c12k38 Small C 457 67 9.0 no
1143 AB2319 c12k54 Small C 419 100 7.0 yes
1146 AB2321 c12k57 Small C 454 51 9.0 yes
1156 AB2331 c12k67 Small C 248 79 2.0 yes
1157 AB2332 c12k68 Small C 434 61 8.0 no
1164 AB2341 c12k75 Small C 431 33 8.0 yes
1168 AB2345 c12k79 Small C 341 76 5.0 yes
1176 AB2353 c12k87 Small C 484 25 10.5 no
1181 AB2358 c12k92 Small C 348 56 5.0 yes
1186 AB2362 c12k97 Small C 382 66 6.0 yes
1197 AB2372 c13k9 Small C 467 84 10.0 no
1209 AB2387 c13k21 Small C 405 52 7.0 no
1265 AB286 c13k77 Small C 143 83 0.5 yes
1281 AB302 c13k93 Small C 204 53 1.0 yes
1288 AB309 c14k1 Small C 101 53 0.5 no
1299 AB320 c14k12 Small C 121 22 0.5 yes
1314 AB335 c14k27 Small C 65 65 0.5 yes
1329 AB350 c14k42 Small C 139 79 0.5 yes
1339 AB360 c14k52 Small C 167 72 1.0 yes
1351 AB372 c14k64 Small C 154 55 1.0 yes
1379 AB400 c14k92 Small C 146 35 0.5 yes
1390 AB411 c15k4 Small C 168 32 1.0 yes
1391 AB412 c15k5 Small C 76 85 0.5 yes
1393 AB414 c15k7 Small C 113 62 0.5 no
1395 AB416 c15k9 Small C 174 36 1.0 no
1402 AB423 c15k16 Small C 300 50 3.0 yes
1409 AB430 c15k23 Small C 276 48 3.0 yes
1412 AB433 c15k26 Small C 232 87 2.0 no
1460 AB481 c15k74 Small C 227 50 2.0 no
1465 AB486 c15k79 Small C 342 40 5.0 no
1467 AB488 c15k81 Small C 195 61 1.0 no
1475 AB496 c15k89 Small C 235 87 2.0 yes
1476 AB497 c15k90 Small C 239 31 2.0 yes
1481 AB502 c15k95 Small C 268 52 3.0 no
1491 AB512 c16k6 Small C 250 75 2.0 yes
1494 AB515 c16k9 Small C 274 44 3.0 no
1500 AB521 c16k15 Small C 270 76 3.0 no
1507 AB528 c16k22 Small C 214 34 1.0 no
1514 AB535 c16k29 Small C 286 41 3.0 yes
1519 AB540 c16k34 Small C 283 65 3.0 no
1522 AB543 c16k37 Small C 318 71 4.0 yes
1526 AB547 c16k41 Small C 202 45 1.0 yes
1532 AB553 c16k47 Small C 308 14 4.0 no
1539 AB560 c16k54 Small C 243 75 2.0 yes
1545 AB566 c16k60 Small C 200 69 1.0 yes
1553 AB623 c16k68 Small D 486 97 10.5 yes
1555 AB640 c16k70 Small D 370 38 6.0 yes
1558 AB661 c16k73 Small D 460 96 9.0 no
1564 AB730 c16k79 Small D 420 101 8.0 yes
1566 AB754 c16k81 Small D 474 97 10.0 no
1573 AB852 c16k88 Small E 480 89 10.0 yes
1575 AB958 c16k90 Small E 490 38 10.5 yes
1584 AB093 c16k99 Medium A 651 42 22.0 no
1590 AB1002 c17k6 Medium A 743 127 27.0 no
1595 AB1007 c17k11 Medium A 740 122 27.0 no
1596 AB1009 c17k12 Medium A 600 44 17.0 yes
1602 AB1015 c17k18 Medium A 834 140 35.0 yes
1616 AB1030 c17k32 Medium A 710 92 26.0 yes
1622 AB1036 c17k38 Medium A 904 77 41.0 yes
1637 AB1055 c17k53 Medium A 550 87 14.0 yes
1652 AB107 c17k68 Medium A 560 72 15.0 yes
1653 AB1070 c17k69 Medium A 820 106 34.0 yes
1657 AB1075 c17k73 Medium A 563 64 15.0 no
1659 AB1077 c17k75 Medium A 611 102 19.0 yes
1661 AB1079 c17k77 Medium A 557 32 14.0 yes
1693 AB1113 c18k10 Medium A 530 61 13.0 yes
1706 AB1134 c18k23 Medium A 619 78 19.0 no
1718 AB1146 c18k35 Medium A 760 84 29.0 no
1719 AB1147 c18k36 Medium A 960 73 44.0 yes
1722 AB1150 c18k39 Medium A 512 92 12.0 no
1723 AB1152 c18k40 Medium A 560 60 15.0 no
1734 AB1164 c18k51 Medium A 753 56 29.0 yes
1737 AB1167 c18k54 Medium A 850 125 36.0 yes
1750 AB1181 c18k67 Medium A 810 120 32.0 no
1755 AB1186 c18k72 Medium A 990 145 47.0 no
1759 AB1190 c18k76 Medium B 556 52 14.0 yes
1765 AB1198 c18k82 Medium B 958 149 44.0 no
1766 AB120 c18k83 Medium B 600 48 18.0 no
1773 AB1207 c18k90 Medium B 920 118 41.0 yes
1776 AB1213 c18k93 Medium B 530 105 13.0 yes
1779 AB1216 c18k96 Medium B 632 112 20.0 no
1793 AB1239 c19k11 Medium B 550 95 14.0 no
1796 AB1243 c19k14 Medium B 540 74 13.0 yes
1807 AB1256 c19k25 Medium B 618 70 19.0 yes
1824 AB1273 c19k42 Medium B 621 43 19.0 yes
1829 AB1278 c19k47 Medium B 804 103 32.0 no
1831 AB1280 c19k49 Medium B 963 106 45.0 yes
1835 AB1285 c19k53 Medium B 669 79 22.0 yes
1845 AB1296 c19k63 Medium B 674 47 23.0 yes
1847 AB1298 c19k65 Medium B 619 46 19.0 yes
1851 AB1302 c19k69 Medium B 944 131 43.0 no
1852 AB1303 c19k70 Medium B 503 91 12.0 yes
1862 AB1315 c19k80 Medium B 915 129 41.0 yes
1863 AB1316 c19k81 Medium B 649 117 21.0 no
1864 AB1318 c19k82 Medium B 511 104 12.0 yes
1867 AB1321 c19k85 Medium B 619 94 19.0 yes
1873 AB1327 c19k91 Medium B 500 42 11.0 yes
1877 AB1331 c19k95 Medium B 960 78 45.0 yes
1883 AB1942 c20k2 Medium C 560 84 14.0 yes
1894 AB2031 c20k13 Medium C 540 74 13.0 no
1920 AB2179 c20k39 Medium C 579 49 16.0 yes
1929 AB2227 c20k48 Medium C 512 92 12.0 no
1931 AB2238 c20k50 Medium C 540 66 13.0 no
1948 AB2378 c20k67 Medium C 510 48 12.0 yes
1950 AB2382 c20k69 Medium C 553 96 14.0 yes
1962 AB580 c20k81 Medium C 550 67 14.0 yes
1967 AB585 c20k86 Medium C 620 79 19.0 no
1969 AB587 c20k88 Medium C 660 118 22.0 no
1971 AB589 c20k90 Medium C 580 70 16.0 yes
1977 AB597 c20k96 Medium C 570 73 15.0 yes
1988 AB611 c22k8 Medium C 640 69 21.0 no
1990 AB613 c22k10 Medium D 725 89 27.0 yes
2039 AB672 c22k59 Medium D 500 99 11.0 no
2047 AB682 c22k67 Medium D 650 81 22.0 yes
2048 AB683 c22k68 Medium D 656 90 22.0 no
2055 AB690 c22k75 Medium D 750 95 28.0 yes
2074 AB710 c22k94 Medium D 630 75 20.0 yes
2077 AB713 c22k97 Medium D 590 55 16.0 yes
2083 AB719 c23k4 Medium D 630 103 19.0 yes
2084 AB720 c23k5 Medium D 730 129 27.0 yes
2124 AB777 c23k45 Medium D 580 54 16.0 yes
2136 AB789 c23k57 Medium D 790 102 31.0 yes
2145 AB798 c23k66 Medium D 880 120 38.0 no
2147 AB803 c23k68 Medium D 700 66 25.0 yes
2152 AB808 c23k73 Medium D 986 151 46.0 yes
2164 AB821 c23k85 Medium D 674 92 23.0 yes
2166 AB823 c23k87 Medium D 692 93 24.0 yes
2167 AB824 c23k88 Medium D 683 96 23.0 no
2171 AB829 c23k92 Medium D 595 87 17.0 yes
2177 AB836 c23k98 Medium E 590 79 17.0 no
2181 AB840 c24k3 Medium E 694 73 24.0 yes
2196 AB856 c24k18 Medium E 810 113 32.0 no
2199 AB859 c24k21 Medium E 810 105 33.0 yes
2201 AB861 c24k23 Medium E 870 135 38.0 yes
2212 AB875 c24k34 Medium E 850 141 36.0 yes
2228 AB896 c24k50 Medium E 620 98 19.0 yes
2230 AB898 c24k52 Medium E 670 115 23.0 yes
2235 AB903 c24k57 Medium E 850 114 36.0 yes
2252 AB926 c24k74 Medium E 640 100 20.0 yes
2258 AB933 c24k80 Medium E 550 87 14.0 yes
2263 AB938 c24k85 Medium E 520 52 12.0 no
2267 AB942 c24k89 Medium E 610 86 18.0 no
2268 AB943 c24k90 Medium E 610 73 18.0 yes
2269 AB944 c24k91 Medium E 670 95 23.0 yes
2274 AB949 c24k96 Medium E 644 53 21.0 yes
2290 AB970 c25k13 Medium E 809 123 32.0 no
2291 AB971 c25k14 Medium E 735 110 27.0 yes
2299 AB979 c25k22 Medium E 960 138 45.0 yes
2303 AB989 c25k26 Medium E 852 142 36.0 no
2309 AB995 c25k32 Medium E 550 51 14.0 no
2310 AB996 c25k33 Medium E 581 102 16.0 yes
2311 AB997 c25k34 Medium E 590 75 16.0 no
2315 AB098 c25k38 Big A 1155 117 62.0 yes
2316 AB1008 c25k39 Big A 1390 171 77.0 yes
2318 AB1028 c25k41 Big A 1193 122 63.0 yes
2319 AB1029 c25k42 Big A 1110 97 58.0 yes
2323 AB1041 c25k46 Big A 1100 109 58.0 yes
2324 AB1042 c25k47 Big A 1100 161 57.0 yes
2325 AB1072 c25k48 Big A 1434 157 83.0 yes
2326 AB1084 c25k49 Big A 1396 172 82.0 no
2327 AB1093 c25k50 Big A 1063 146 54.0 yes
2328 AB1094 c25k51 Big A 1153 144 62.0 yes
2329 AB1096 c25k52 Big A 1620 232 152.0 no
2330 AB1108 c25k53 Big A 1094 83 57.0 yes
2331 AB1116 c25k54 Big A 1090 137 55.0 yes
2332 AB1117 c25k55 Big A 1315 170 70.0 yes
2333 AB1123 c25k56 Big A 1020 133 50.0 yes
2334 AB1124 c25k57 Big A 1130 126 59.0 yes
2335 AB1125 c25k58 Big A 1450 133 94.0 yes
2336 AB1126 c25k59 Big A 1614 159 138.0 yes
2337 AB1130 c25k60 Big A 1080 140 54.0 yes
2338 AB1132 c25k61 Big A 2510 258 305.0 yes
2339 AB1148 c25k62 Big A 1230 140 64.0 yes
2340 AB1153 c25k63 Big A 1121 146 59.0 yes
2341 AB1172 c25k64 Big A 1440 133 84.0 yes
2343 AB1187 c25k66 Big A 1459 176 99.0 no
2347 AB1211 c25k70 Big B 1050 142 52.0 yes
2348 AB1212 c25k71 Big B 1616 158 142.0 yes
2349 AB1217 c25k72 Big B 1101 117 58.0 yes
2350 AB1220 c25k73 Big B 1480 193 104.0 no
2351 AB1231 c25k74 Big B 1160 121 62.0 no
2352 AB1232 c25k75 Big B 1490 201 105.0 yes
2353 AB1251 c25k76 Big B 1003 147 49.0 yes
2354 AB1283 c25k77 Big B 1510 163 107.0 yes
2355 AB1308 c25k78 Big B 1170 158 63.0 no
2356 AB1317 c25k79 Big B 1030 122 51.0 no
2357 AB590 c25k80 Big C 1360 134 76.0 yes
2358 AB636 c25k81 Big D 1024 149 50.0 yes
2359 AB637 c25k82 Big D 1405 111 83.0 yes
2360 AB670 c25k83 Big D 1600 189 112.0 yes
2361 AB725 c25k84 Big D 1005 83 49.0 yes
2362 AB727 c25k85 Big D 1450 162 94.0 yes
2363 AB741 c25k86 Big D 1093 119 56.0 no
2364 AB742 c25k87 Big D 1030 149 50.0 yes
2365 AB744 c25k88 Big D 1370 182 77.0 no
2367 AB746 c25k90 Big D 1090 105 55.0 yes
2368 AB747 c25k91 Big D 1280 145 65.0 yes
2369 AB748 c25k92 Big D 1300 172 68.0 yes
2370 AB749 c25k93 Big D 1911 263 196.0 yes
2372 AB767 c25k95 Big D 1300 176 68.0 yes
2373 AB799 c25k96 Big D 1094 131 56.0 no
2374 AB862 c25k97 Big E 1010 132 50.0 yes
2375 AB863 c25k98 Big E 1565 162 109.0 no
2376 AB864 c25k99 Big E 1360 126 73.0 yes
2378 AB891 c26k2 Big E 1040 118 52.0 no
2379 AB892 c26k3 Big E 1084 92 54.0 yes
2380 AB893 c26k4 Big E 1551 168 107.0 no
2381 AB904 c26k5 Big E 1035 86 51.0 yes
2382 AB905 c26k6 Big E 1405 110 83.0 no
2383 AB906 c26k7 Big E 1250 100 64.0 yes
2384 AB908 c26k8 Big E 1305 150 70.0 yes
2385 AB912 c26k9 Big E 1088 133 55.0 no
2386 AB916 c26k10 Big E 1161 157 62.0 no
2387 AB932 c26k11 Big E 1360 104 72.0 yes
2388 AB953 c26k12 Big E 1085 116 54.0 no
2389 AB956 c26k13 Big E 1040 78 51.0 yes
2390 AB957 c26k14 Big E 1220 163 63.0 no
2391 AB983 c26k15 Big E 1030 145 51.0 yes
2392 AB984 c26k16 Big E 1020 89 50.0 yes
2394 AB986 c26k18 Big E 1297 161 67.0 no
2395 AB987 c26k19 Big E 1640 225 169.0 yes
2396 AB988 c26k20 Big E 1860 253 176.0 yes
[1] 370 8
[1] 0.10142741 0.22511936 0.05689830 0.23254088 0.08163669 0.04452910
[7] 0.20780249 0.10884892 0.06926750 0.18801178 0.23501472 0.20285481
[13] 0.05937214 0.19543329 0.24243624 0.07421517 0.12121812 0.12369196
[19] 0.07916285 0.17069490 0.08905821 0.23748856 0.09647973 0.03958143
[25] 0.11874428 0.13606115 0.14595651 0.03463375 0.17069490 0.11874428
[31] 0.12369196 0.20038097 0.21769785 0.08163669 0.23748856 0.19295945
[37] 0.17316874 0.18059026 0.13111348 0.11132276 0.21522401 0.12616580
[43] 0.12121812 0.20285481 0.17564258 0.16822106 0.22017168 0.18801178
[49] 0.21027633 0.21027633 0.04452910 0.13358731 0.18059026 0.10884892
[55] 0.06679366 0.11132276 0.05689830 0.18801178 0.04700294 0.08658437
[61] 0.13853499 0.20038097 0.14595651 0.15832571 0.15832571 0.18059026
[67] 0.19048561 0.19295945 0.22017168 0.16574722 0.14595651 0.10637508
[73] 0.21027633 0.13111348 0.10884892 0.07668901 0.11132276 0.15090419
[79] 0.20285481 0.21522401 0.01731687 0.13853499 0.20285481 0.05442446
[85] 0.20285481 0.13853499 0.18059026 0.07421517 0.17564258 0.11874428
[91] 0.22759320 0.13853499 0.06679366 0.09400589 0.23501472 0.22017168
[97] 0.06926750 0.17316874 0.07668901 0.23254088 0.22759320 0.23501472
[103] 0.23996240 0.11627044 0.21522401 0.13358731 0.09647973 0.21027633
[109] 0.23748856 0.04947678 0.18801178 0.24985775 0.09153205 0.09647973
[115] 0.22759320 0.23501472 0.07421517 0.22511936 0.14843035 0.19790713
[121] 0.16327338 0.07174134 0.25975311 0.08905821 0.21769785 0.15585187
[127] 0.18553794 0.17316874 0.16822106 0.13358731 0.18306410 0.05689830
[133] 0.17069490 0.05937214 0.10142741 0.10142741 0.17069490 0.13111348
[139] 0.12863964 0.18059026 0.21522401 0.17316874 0.15090419 0.13358731
[145] 0.15090419 0.14100883 0.19543329 0.06679366 0.16574722 0.24738392
[151] 0.12616580 0.19543329 0.15090419 0.08163669 0.18801178 0.06184598
[157] 0.13853499 0.16327338 0.20780249 0.12863964 0.20532865 0.13111348
[163] 0.13111348 0.05442446 0.16079954 0.19543329 0.17811642 0.13606115
[169] 0.08658437 0.07916285 0.21027633 0.15337803 0.08905821 0.12369196
[175] 0.11874428 0.21522401 0.12369196 0.09895357 0.15090419 0.21522401
[181] 0.07668901 0.12863964 0.18553794 0.10884892 0.18801178 0.08411053
[187] 0.10142741 0.16079954 0.17564258 0.11132276 0.03463375 0.18553794
[193] 0.17069490 0.23996240 0.09400589 0.23748856 0.24985775 0.23996240
[199] 0.22017168 0.09400589 0.07041899 0.21293362 0.20455041 0.07377228
[205] 0.23472998 0.15425113 0.12910149 0.14586791 0.12071827 0.17772413
[211] 0.10730513 0.17101755 0.05365257 0.10227520 0.13077813 0.14083799
[217] 0.12239492 0.15425113 0.10059856 0.09389199 0.20958034 0.20119712
[223] 0.24311319 0.08718542 0.24981976 0.08047885 0.19784384 0.17604748
[229] 0.18778398 0.15928106 0.12407156 0.11736499 0.07209564 0.17269420
[235] 0.17772413 0.13245477 0.07880221 0.07712556 0.21964019 0.15257448
[241] 0.21628691 0.19616719 0.17437084 0.15760441 0.07041899 0.13077813
[247] 0.14083799 0.12407156 0.08215549 0.15425113 0.11065842 0.08047885
[253] 0.16095770 0.11233506 0.13245477 0.19784384 0.11736499 0.12239492
[259] 0.11568835 0.14922120 0.16598763 0.13580806 0.15089784 0.15928106
[265] 0.12574820 0.09221535 0.17269420 0.21628691 0.09053871 0.17101755
[271] 0.20119712 0.11065842 0.25317305 0.15425113 0.15592777 0.16095770
[277] 0.14586791 0.13245477 0.12239492 0.18946062 0.17604748 0.22634676
[283] 0.23640662 0.16431098 0.19281391 0.19113727 0.16766427 0.14586791
[289] 0.08718542 0.14419127 0.12239492 0.15928106 0.08886206 0.20622705
[295] 0.18443070 0.23137669 0.23808326 0.08550878 0.17101755 0.12574820
[301] 0.77411910 1.00000000 0.80720111 0.64179104 0.72118788 1.00000000
[307] 1.00000000 1.00000000 0.96599477 0.95276196 1.00000000 0.54916141
[313] 0.90644715 1.00000000 0.87998154 0.83366672 0.87998154 1.00000000
[319] 0.92629635 1.00000000 0.92629635 0.96599477 0.87998154 1.00000000
[325] 0.93952916 1.00000000 0.77411910 1.00000000 0.80058471 1.00000000
[331] 0.97261117 1.00000000 1.00000000 0.80720111 0.88659794 0.98584398
[337] 0.73442068 1.00000000 0.54916141 1.00000000 0.78735190 0.98584398
[343] 1.00000000 0.69472226 0.95937837 1.00000000 1.00000000 1.00000000
[349] 0.86674873 0.87336513 1.00000000 0.83366672 0.78073550 0.60870903
[355] 1.00000000 0.56901062 0.72780428 0.66164025 0.99246038 0.87998154
[361] 1.00000000 0.68810586 0.76750269 0.51607940 1.00000000 0.95937837
[367] 0.58885982 1.00000000 1.00000000 1.00000000
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