data/NURE.R
In brian-j-smith/ramps: Bayesian Geostatistical Modeling with RAMPS
NURE <- structure(list(ppm = c(2.84, 2.24, 2.1, 2.4, 2.58, 2.65, 2.34,
2.35, 6.1, 6.1, 4, 5.7, 5.6, 4.8, 6.4, 4.6, 8.9, 5.9, 5.1, 11.6,
6.8, 10.9, 5, 11.3, 6.5, 8, 11.4, 7.1, 11, 2.2, 5.4, 6.1, 5.6,
14.9, 4, 4.2, 10.7, 8.7, 6.3, 6.9, 14.8, 6.8, 5.8, 6.2, 4.7,
5.9, 4.9, 3.7, 4.7, 4.5, 4.6, 7, 4, 9, 2.2, 8.5, 5.5, 4.4, 16.3,
6.1, 12.2, 6.4, 5, 6.4, 3.8, 6.1, 4.4, 8.4, 9.9, 4.6, 7.5, 3.6,
3.9, 4.1, 5.3, 3.7, 7.5, 4.1, 4.8, 5, 6.4, 3.3, 8.9, 5.3, 4.4,
5.7, 6.4, 3.3, 3.7, 3.9, 4, 3.2, 3.4, 3.3, 2.6, 4.5, 4.9, 4.6,
3.4, 3, 4.6, 5.2, 24.9, 7.4, 8.8, 3, 3.9, 5.9, 6.6, 9.6, 7.6,
8.1, 6, 5.5, 5, 5.8, 10.4, 25.1, 6.1, 6.7, 5.9, 5.5, 4.5, 4.5,
4.2, 5.6, 7, 5, 4.5, 3.6, 4.4, 4.6, 10, 5.3, 4.9, 3.6, 5.1, 3.7,
6.7, 4.7, 2.9, 3.8, 4.9, 4.3, 6.4, 6.9, 2.6, 3.5, 3.5, 1.8, 4.8,
2.9, 3.1, 1.6, 2.4, 6.9, 4.3, 3.8, 4.4, 3.1, 3.4, 4.6, 8.7, 2.5,
23.1, 5.1, 4, 5.8, 1.7, 10, 5.3, 4.4, 4.8, 8.5, 4.6, 4.1, 5.6,
5.3, 5, 4.7, 3.7, 7, 3.4, 4.3, 9.4, 3.5, 7.3, 3, 4.3, 4.1, 4.3,
3.4, 6.3, 4, 3.7, 5.3, 4.2, 4, 4.6, 3, 4.9, 5.4, 3.6, 10.4, 8,
14.8, 9.5, 6.2, 6.4, 3.7, 6.9, 7.6, 3.2, 7, 8.3, 2.6, 6.6, 5.5,
6.9, 5, 3.7, 5.4, 11.6, 8.4, 3.1, 5.6, 5.1, 3.9, 5.7, 12.8, 3.5,
7, 11.2, 7, 3.2, 10.5, 2.6, 9.3, 4.1, 3.6, 3.7, 4.5, 8.2, 5,
5.6, 3.2, 5.9, 4.7, 5.1, 2, 9, 3.4, 12.4, 13.1, 2.1, 4.6, 4.5,
3.4, 4.3, 5.5, 6.6, 4.4, 3.6, 2.8, 4.5, 3.5, 5.3, 3, 3.7, 3.9,
5.6, 3.2, 5.1, 7.6, 9.5, 7.8, 6.6, 7.2, 5.5, 4.6, 3.2, 6.8, 6.7,
5.3, 4.3, 6.9, 3.9, 8.9, 5.3, 5.8, 7, 6.8, 8.4, 6.8, 7.4, 3.5,
5.8, 5.9), measurement = c(1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
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2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
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2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), lon = c(NA, NA, NA, NA,
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brian-j-smith/ramps documentation built on Feb. 2, 2023, 5:54 a.m.
R Package Documentation
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NURE <- structure(list(ppm = c(2.84, 2.24, 2.1, 2.4, 2.58, 2.65, 2.34,
2.35, 6.1, 6.1, 4, 5.7, 5.6, 4.8, 6.4, 4.6, 8.9, 5.9, 5.1, 11.6,
6.8, 10.9, 5, 11.3, 6.5, 8, 11.4, 7.1, 11, 2.2, 5.4, 6.1, 5.6,
14.9, 4, 4.2, 10.7, 8.7, 6.3, 6.9, 14.8, 6.8, 5.8, 6.2, 4.7,
5.9, 4.9, 3.7, 4.7, 4.5, 4.6, 7, 4, 9, 2.2, 8.5, 5.5, 4.4, 16.3,
6.1, 12.2, 6.4, 5, 6.4, 3.8, 6.1, 4.4, 8.4, 9.9, 4.6, 7.5, 3.6,
3.9, 4.1, 5.3, 3.7, 7.5, 4.1, 4.8, 5, 6.4, 3.3, 8.9, 5.3, 4.4,
5.7, 6.4, 3.3, 3.7, 3.9, 4, 3.2, 3.4, 3.3, 2.6, 4.5, 4.9, 4.6,
3.4, 3, 4.6, 5.2, 24.9, 7.4, 8.8, 3, 3.9, 5.9, 6.6, 9.6, 7.6,
8.1, 6, 5.5, 5, 5.8, 10.4, 25.1, 6.1, 6.7, 5.9, 5.5, 4.5, 4.5,
4.2, 5.6, 7, 5, 4.5, 3.6, 4.4, 4.6, 10, 5.3, 4.9, 3.6, 5.1, 3.7,
6.7, 4.7, 2.9, 3.8, 4.9, 4.3, 6.4, 6.9, 2.6, 3.5, 3.5, 1.8, 4.8,
2.9, 3.1, 1.6, 2.4, 6.9, 4.3, 3.8, 4.4, 3.1, 3.4, 4.6, 8.7, 2.5,
23.1, 5.1, 4, 5.8, 1.7, 10, 5.3, 4.4, 4.8, 8.5, 4.6, 4.1, 5.6,
5.3, 5, 4.7, 3.7, 7, 3.4, 4.3, 9.4, 3.5, 7.3, 3, 4.3, 4.1, 4.3,
3.4, 6.3, 4, 3.7, 5.3, 4.2, 4, 4.6, 3, 4.9, 5.4, 3.6, 10.4, 8,
14.8, 9.5, 6.2, 6.4, 3.7, 6.9, 7.6, 3.2, 7, 8.3, 2.6, 6.6, 5.5,
6.9, 5, 3.7, 5.4, 11.6, 8.4, 3.1, 5.6, 5.1, 3.9, 5.7, 12.8, 3.5,
7, 11.2, 7, 3.2, 10.5, 2.6, 9.3, 4.1, 3.6, 3.7, 4.5, 8.2, 5,
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"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,new london", "connecticut,new london",
"connecticut,new london", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,tolland", "connecticut,tolland", "connecticut,tolland",
"connecticut,windham", "connecticut,windham", "connecticut,windham",
"connecticut,windham", "connecticut,windham", "connecticut,windham",
"connecticut,windham", "connecticut,windham", "connecticut,windham",
"connecticut,windham", "connecticut,windham", "connecticut,windham",
"connecticut,windham", "connecticut,windham", "connecticut,windham",
"connecticut,windham", "connecticut,windham", "connecticut,windham"
), area = c(836.96, 750.57, 944.57, 439.07, 862.02, 771.66, 417.01,
521.47, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96,
836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96,
836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96,
836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 836.96,
836.96, 836.96, 836.96, 836.96, 836.96, 836.96, 750.57, 750.57,
750.57, 750.57, 750.57, 750.57, 750.57, 750.57, 750.57, 750.57,
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750.57, 750.57, 750.57, 750.57, 750.57, 750.57, 750.57, 750.57,
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750.57, 750.57, 750.57, 750.57, 750.57, 750.57, 944.57, 944.57,
944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57,
944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57,
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944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57, 944.57,
439.07, 439.07, 439.07, 439.07, 439.07, 439.07, 439.07, 439.07,
439.07, 439.07, 439.07, 439.07, 439.07, 439.07, 439.07, 439.07,
439.07, 439.07, 439.07, 439.07, 862.02, 862.02, 862.02, 862.02,
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862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02,
862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02,
862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02, 862.02,
862.02, 862.02, 862.02, 862.02, 771.66, 771.66, 771.66, 771.66,
771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66,
771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66,
771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66, 771.66,
771.66, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01,
417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01,
417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01,
417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01, 417.01,
417.01, 521.47, 521.47, 521.47, 521.47, 521.47, 521.47, 521.47,
521.47, 521.47, 521.47, 521.47, 521.47, 521.47, 521.47, 521.47,
521.47, 521.47, 521.47), id = c(1, 2, 3, 4, 5, 6, 7, 8, 45, 50,
53, 54, 51, 44, 57, 58, 46, 47, 48, 49, 23, 24, 52, 26, 27, 55,
56, 43, 30, 31, 32, 220, 34, 35, 36, 37, 25, 39, 40, 28, 29,
38, 33, 42, 41, 9, 10, 11, 12, 93, 94, 95, 96, 97, 98, 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,
101, 102, 99, 100, 13, 14, 15, 16, 17, 138, 103, 104, 105, 106,
107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119,
120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132,
133, 134, 135, 136, 137, 151, 139, 140, 141, 142, 143, 144, 145,
146, 147, 148, 149, 150, 155, 152, 153, 154, 159, 156, 157, 158,
163, 160, 161, 162, 165, 166, 169, 170, 164, 173, 174, 171, 181,
177, 178, 179, 167, 180, 182, 183, 184, 172, 175, 176, 186, 187,
203, 204, 205, 206, 168, 208, 209, 210, 211, 212, 213, 214, 215,
216, 217, 218, 219, 207, 221, 222, 223, 224, 185, 199, 200, 188,
189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 201, 202, 246,
245, 250, 244, 253, 227, 251, 252, 243, 230, 231, 247, 248, 249,
22, 236, 237, 225, 239, 240, 228, 229, 234, 235, 232, 233, 238,
241, 242, 18, 257, 258, 19, 20, 21, 262, 263, 264, 265, 266,
254, 255, 256, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279,
280, 268, 269, 260, 261, 259, 282, 281, 226, 267, 283, 284, 285,
286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298
)), .Names = c("ppm", "measurement", "lon", "lat", "easting",
"northing", "county", "area", "id"), row.names = c(NA, 298L), class = "data.frame")
NURE.grid <- structure(list(lon = c(-73.6394752437233, -73.5564697135208,
-73.4734641833183, -73.5564697135208, -73.4734641833183, -73.3904586531158,
-73.3074531229133, -73.2244475927108, -73.1414420625083, -73.4734641833183,
-73.3904586531158, -73.3074531229133, -73.2244475927108, -73.1414420625083,
-73.0584365323059, -73.4734641833183, -73.3904586531158, -73.3074531229133,
-73.2244475927108, -73.1414420625083, -73.0584365323059, -72.9754310021034,
-72.8924254719009, -72.8094199416984, -72.7264144114959, -72.6434088812934,
-72.5604033510909, -72.4773978208884, -72.3943922906859, -72.3113867604834,
-73.4734641833183, -73.3904586531158, -73.3074531229133, -73.2244475927108,
-73.1414420625083, -73.0584365323059, -72.9754310021034, -72.8924254719009,
-72.8094199416984, -72.7264144114959, -72.6434088812934, -72.5604033510909,
-72.4773978208884, -72.3943922906859, -72.3113867604834, -72.228381230281,
-72.1453757000785, -72.062370169876, -71.9793646396735, -71.896359109471,
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-73.1414420625083, -73.0584365323059, -72.9754310021034, -72.8924254719009,
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-72.4773978208884, -72.3943922906859, -72.3113867604834, -72.228381230281,
-72.1453757000785, -72.062370169876, -71.9793646396735, -71.896359109471,
-71.8133535792685, -73.4734641833183, -73.3904586531158, -73.3074531229133,
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-72.1453757000785, -72.062370169876, -71.9793646396735, -71.896359109471,
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-72.1453757000785, -72.062370169876, -71.9793646396735, -71.896359109471,
-71.8133535792685), lat = c(41.0833488882405, 41.0833488882405,
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8L, 8L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L,
7L, 7L, 8L, 8L, 8L, 8L, 8L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L,
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3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
8L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 7L, 7L,
7L, 7L, 8L, 8L, 8L, 8L)), .Names = c("lon", "lat", "id"), class = "data.frame", row.names = c(NA,
239L))
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