* using log directory ‘/data/gannet/ripley/R/packages/tests-LENGTH1/vortexR.Rcheck’ * using R Under development (unstable) (2022-04-03 r82074) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-stop-on-test-error’ * checking for file ‘vortexR/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘vortexR’ version ‘1.1.7’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for executable files ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘vortexR’ can be installed ... [18s/47s] OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... [20s/20s] OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd line widths ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking installed files from ‘inst/doc’ ... OK * checking files in ‘vignettes’ ... OK * checking examples ... [13s/13s] OK * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘testthat.R’ ERROR Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(vortexR) > > test_check("vortexR") Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0 0.0 380.5 441.7 779.8 1544.0 Initialization... TASK: Diagnostic of candidate set. Sample size: 150 0 factor(s). 3 covariate(s). 0 f exclusion(s). 0 c exclusion(s). 0 f:f exclusion(s). 0 c:c exclusion(s). 0 f:c exclusion(s). Size constraints: min = 0 max = -1 Complexity constraints: min = 0 max = -1 Your candidate set contains 64 models. TASK: Genetic algorithm in the candidate set. Initialization... Algorithm started... Improvements in best and average IC have bebingo en below the specified goals. Algorithm is declared to have converged. Completed. user system elapsed 0.715 0.022 0.488 Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.8112 0.9536 0.9691 0.9584 0.9778 0.9887 62 logit probit cloglog cauchit loglog 0.4762035 0.2225278 0.0000000 3.3530873 0.5069589 Initialization... TASK: Diagnostic of candidate set. Sample size: 88 0 factor(s). 3 covariate(s). 0 f exclusion(s). 0 c exclusion(s). 0 f:f exclusion(s). 0 c:c exclusion(s). 0 f:c exclusion(s). Size constraints: min = 0 max = -1 Complexity constraints: min = 0 max = -1 Your candidate set contains 64 models. TASK: Genetic algorithm in the candidate set. Initialization... Algorithm started... ----------- FAILURE REPORT -------------- --- failure: length > 1 in coercion to logical --- --- srcref --- : --- package (from environment) --- glmulti --- call from context --- glmulti(y = "GeneDiv", data = list(Population = c("Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1"), Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 37L, 37L, 37L, 38L, 38L, 38L, 39L, 39L, 39L, 40L, 40L, 40L, 41L, 41L, 41L, 42L, 42L, 42L, 43L, 43L, 43L, 44L, 44L, 44L, 45L, 45L, 45L, 46L, 46L, 46L, 47L, 47L, 47L, 48L, 48L, 48L, 49L, 49L, 49L, 50L, 50L, 50L), Iteration = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3), YrExt = c(8, 12, 13, NA, NA, NA, NA, NA, NA, 7, 5, 4, 19, 19, 32, 11, 13, 15, 79, 54, 83, 70, 24, 23, NA, NA, NA, 32, 34, 99, NA, NA, NA, NA, NA, NA, 33, 36, 24, NA, NA, NA, NA, NA, NA, 11, 8, 11, NA, NA, NA, 12, 4, 6, 9, 9, 10, 9, 9, 12, NA, NA, NA, NA, NA, NA, 36, 19, 30, NA, 101, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, 18, 13, NA, NA, NA, 15, 24, 21, 7, 10, 10, NA, NA, NA, 29, 24, 22, NA, NA, NA, 31, 55, 20, 33, 39, 35, 48, 50, 30, NA, NA, NA, 109, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), N = c(0, 0, 0, 1384, 1514, 605, 1364, 1366, 1108, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 13, 3, 18, 0, 0, 382, 722, 386, 0, 0, 15, 785, 814, 809, 1253, 1330, 1290, 0, 0, 0, 557, 588, 527, 385, 552, 580, 0, 0, 0, 1166, 1057, 1098, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1106, 1271, 1544, 538, 587, 541, 0, 0, 0, 88, 12, 232, 1087, 1126, 1218, 438, 390, 418, 465, 465, 437, 464, 244, 353, 408, 468, 419, 461, 291, 79, 930, 1010, 764, 663, 580, 678, 781, 796, 847, 476, 577, 603, 355, 187, 879, 0, 0, 0, 982, 996, 884, 0, 0, 0, 0, 0, 0, 1466, 1429, 1464, 0, 0, 0, 755, 731, 776, 0, 0, 0, 0, 0, 10, 0, 0, 0, 1243, 1136, 1216, 23, 52, 379, 213, 183, 81, 682, 681, 690, 1197, 1036, 993), GeneDiv = c(NA, NA, NA, 0.9605, 0.9372, 0.8284, 0.9883, 0.9839, 0.9823, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9339, 0.9538, 0.9679, NA, NA, NA, 0.9674, 0.9658, 0.971, 0.9864, 0.9845, 0.9861, NA, NA, NA, 0.9709, 0.9736, 0.9732, 0.9575, 0.9549, 0.9635, NA, NA, NA, 0.9756, 0.9755, 0.9763, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9642, 0.9636, 0.9632, 0.9716, 0.9713, 0.9664, NA, NA, NA, 0.8917, NA, 0.9211, 0.9744, 0.9703, 0.9742, 0.9634, 0.958, 0.9211, 0.9588, 0.9734, 0.9556, 0.9707, 0.9585, 0.9744, 0.9528, 0.9499, 0.9727, 0.9291, 0.8715, 0.9101, 0.983, 0.9845, 0.9861, 0.9808, 0.9728, 0.9803, 0.9715, 0.9645, 0.9447, 0.9742, 0.9751, 0.9792, 0.9282, 0.9366, 0.9445, NA, NA, NA, 0.9855, 0.9838, 0.9837, NA, NA, NA, NA, NA, NA, 0.9883, 0.988, 0.9882, NA, NA, NA, 0.9612, 0.9546, 0.9663, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9709, 0.9795, 0.9774, NA, 0.86, 0.9333, 0.9194, 0.8876, 0.8112, 0.9502, 0.955, 0.9524, 0.9884, 0.9887, 0.9875), Inbreed = c(NA, NA, NA, 0.0376, 0.0707, 0.1835, 0.011, 0.0205, 0.0162, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0628, 0.0402, 0.0181, NA, NA, NA, 0.0217, 0.0319, 0.0334, 0.016, 0.018, 0.0116, NA, NA, NA, 0.0215, 0.0221, 0.0285, 0.0286, 0.0489, 0.0362, NA, NA, NA, 0.0232, 0.0237, 0.0246, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0407, 0.0393, 0.0298, 0.0353, 0.0187, 0.0314, NA, NA, NA, 0.0909, NA, 0.0776, 0.0313, 0.0284, 0.0263, 0.0137, 0.0359, 0.0622, 0.0409, 0.0129, 0.0526, 0.0302, 0.0492, 0.0283, 0.0515, 0.0769, 0.0167, 0.0651, 0.1375, 0.1013, 0.0183, 0.0149, 0.0196, 0.0226, 0.0276, 0.0206, 0.032, 0.0226, 0.0626, 0.0336, 0.0191, 0.0116, 0.062, 0.0802, 0.0478, NA, NA, NA, 0.0102, 0.005, 0.0147, NA, NA, NA, NA, NA, NA, 0.0109, 0.014, 0.0075, NA, NA, NA, 0.0477, 0.0451, 0.0245, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0241, 0.0194, 0.0214, NA, 0.0962, 0.058, 0.0704, 0.1475, 0.2222, 0.0469, 0.0426, 0.0348, 0.0109, 0.0068, 0.0111), Alleles = c(NA, NA, NA, 51, 31, 12, 146, 113, 119, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, 42, 46, NA, NA, NA, 62, 64, 71, 127, 125, 124, NA, NA, NA, 67, 68, 63, 39, 49, 50, NA, NA, NA, 77, 74, 80, NA, NA, NA, NA, NA, NA, NA, NA, NA, 48, 47, 59, 65, 55, 50, NA, NA, NA, 11, NA, 23, 69, 68, 62, 42, 41, 29, 42, 60, 47, 55, 38, 61, 47, 44, 61, 23, 14, 16, 112, 118, 124, 87, 74, 88, 58, 46, 41, 74, 73, 81, 34, 24, 32, NA, NA, NA, 118, 116, 121, NA, NA, NA, NA, NA, NA, 149, 154, 160, NA, NA, NA, 49, 34, 61, NA, NA, NA, NA, NA, NA, NA, NA, NA, 61, 89, 80, NA, 10, 26, 21, 21, 13, 38, 40, 39, 157, 156, 134 ), SV1 = c(1540.8163, 1540.8163, 1540.8163, 1755.102, 1755.102, 1755.102, 1571.4286, 1571.4286, 1571.4286, 1204.0816, 1204.0816, 1204.0816, 744.898, 744.898, 744.898, 989.7959, 989.7959, 989.7959, 1602.0408, 1602.0408, 1602.0408, 1387.7551, 1387.7551, 1387.7551, 1663.2653, 1663.2653, 1663.2653, 1938.7755, 1938.7755, 1938.7755, 897.9592, 897.9592, 897.9592, 1265.3061, 1265.3061, 1265.3061, 1479.5918, 1479.5918, 1479.5918, 591.8367, 591.8367, 591.8367, 1785.7143, 1785.7143, 1785.7143, 1020.4082, 1020.4082, 1020.4082, 1173.4694, 1173.4694, 1173.4694, 2000, 2000, 2000, 1081.6327, 1081.6327, 1081.6327, 1969.3878, 1969.3878, 1969.3878, 1816.3265, 1816.3265, 1816.3265, 653.0612, 653.0612, 653.0612, 775.5102, 775.5102, 775.5102, 1877.551, 1877.551, 1877.551, 1295.9184, 1295.9184, 1295.9184, 561.2245, 561.2245, 561.2245, 530.6122, 530.6122, 530.6122, 1357.1429, 1357.1429, 1357.1429, 500, 500, 500, 714.2857, 714.2857, 714.2857, 959.1837, 959.1837, 959.1837, 683.6735, 683.6735, 683.6735, 867.3469, 867.3469, 867.3469, 622.449, 622.449, 622.449, 1908.1633, 1908.1633, 1908.1633, 1142.8571, 1142.8571, 1142.8571, 1051.0204, 1051.0204, 1051.0204, 1112.2449, 1112.2449, 1112.2449, 1693.8776, 1693.8776, 1693.8776, 1418.3673, 1418.3673, 1418.3673, 1846.9388, 1846.9388, 1846.9388, 836.7347, 836.7347, 836.7347, 1724.4898, 1724.4898, 1724.4898, 1510.2041, 1510.2041, 1510.2041, 1632.6531, 1632.6531, 1632.6531, 1326.5306, 1326.5306, 1326.5306, 1448.9796, 1448.9796, 1448.9796, 928.5714, 928.5714, 928.5714, 806.1224, 806.1224, 806.1224, 1234.6939, 1234.6939, 1234.6939), SV2 = c(4.5714, 4.5714, 4.5714, 5.0816, 5.0816, 5.0816, 1.4082, 1.4082, 1.4082, 5.898, 5.898, 5.898, 5.2857, 5.2857, 5.2857, 4.7755, 4.7755, 4.7755, 3.0408, 3.0408, 3.0408, 1.8163, 1.8163, 1.8163, 4.1633, 4.1633, 4.1633, 3.8571, 3.8571, 3.8571, 4.8776, 4.8776, 4.8776, 1.7143, 1.7143, 1.7143, 3.7551, 3.7551, 3.7551, 2.5306, 2.5306, 2.5306, 1.9184, 1.9184, 1.9184, 4.6735, 4.6735, 4.6735, 2.0204, 2.0204, 2.0204, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 3.551, 3.551, 3.551, 5.3878, 5.3878, 5.3878, 4.2653, 4.2653, 4.2653, 6, 6, 6, 4.4694, 4.4694, 4.4694, 3.3469, 3.3469, 3.3469, 3.2449, 3.2449, 3.2449, 4.0612, 4.0612, 4.0612, 2.4286, 2.4286, 2.4286, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 1.102, 1.102, 1.102, 2.2245, 2.2245, 2.2245, 2.8367, 2.8367, 2.8367, 1.6122, 1.6122, 1.6122, 5.5918, 5.5918, 5.5918, 2.9388, 2.9388, 2.9388, 1.2041, 1.2041, 1.2041, 5.6939, 5.6939, 5.6939, 3.9592, 3.9592, 3.9592, 1.3061, 1.3061, 1.3061, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 2.7347, 2.7347, 2.7347, 1.5102, 1.5102, 1.5102, 2.6327, 2.6327, 2.6327, 3.449, 3.449, 3.449, 3.6531, 3.6531, 3.6531, 2.3265, 2.3265, 2.3265, 5.4898, 5.4898, 5.4898, 1, 1, 1), SV3 = c(3.8571, 3.8571, 3.8571, 1.5102, 1.5102, 1.5102, 4.1633, 4.1633, 4.1633, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 5.1837, 5.1837, 5.1837, 4.6735, 4.6735, 4.6735, 5.3878, 5.3878, 5.3878, 3.1429, 3.1429, 3.1429, 3.551, 3.551, 3.551, 1.6122, 1.6122, 1.6122, 2.3265, 2.3265, 2.3265, 3.9592, 3.9592, 3.9592, 2.5306, 2.5306, 2.5306, 4.5714, 4.5714, 4.5714, 4.7755, 4.7755, 4.7755, 3.7551, 3.7551, 3.7551, 4.8776, 4.8776, 4.8776, 5.6939, 5.6939, 5.6939, 6, 6, 6, 1.3061, 1.3061, 1.3061, 1.4082, 1.4082, 1.4082, 3.2449, 3.2449, 3.2449, 2.9388, 2.9388, 2.9388, 2.0204, 2.0204, 2.0204, 2.8367, 2.8367, 2.8367, 1.7143, 1.7143, 1.7143, 4.4694, 4.4694, 4.4694, 1.9184, 1.9184, 1.9184, 2.2245, 2.2245, 2.2245, 1.8163, 1.8163, 1.8163, 1.2041, 1.2041, 1.2041, 2.7347, 2.7347, 2.7347, 3.3469, 3.3469, 3.3469, 1, 1, 1, 5.898, 5.898, 5.898, 4.3673, 4.3673, 4.3673, 3.6531, 3.6531, 3.6531, 5.2857, 5.2857, 5.2857, 2.1224, 2.1224, 2.1224, 5.4898, 5.4898, 5.4898, 2.4286, 2.4286, 2.4286, 5.0816, 5.0816, 5.0816, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 2.6327, 2.6327, 2.6327, 3.0408, 3.0408, 3.0408, 4.2653, 4.2653, 4.2653, 1.102, 1.102, 1.102, 4.0612, 4.0612, 4.0612), SV4 = c(5.2857, 5.2857, 5.2857, 1.102, 1.102, 1.102, 3.551, 3.551, 3.551, 2.8367, 2.8367, 2.8367, 3.3469, 3.3469, 3.3469, 2.9388, 2.9388, 2.9388, 1.3061, 1.3061, 1.3061, 5.4898, 5.4898, 5.4898, 1.4082, 1.4082, 1.4082, 2.7347, 2.7347, 2.7347, 1.8163, 1.8163, 1.8163, 3.6531, 3.6531, 3.6531, 4.2653, 4.2653, 4.2653, 2.3265, 2.3265, 2.3265, 3.7551, 3.7551, 3.7551, 3.9592, 3.9592, 3.9592, 1.9184, 1.9184, 1.9184, 5.7959, 5.7959, 5.7959, 6, 6, 6, 5.3878, 5.3878, 5.3878, 3.2449, 3.2449, 3.2449, 5.0816, 5.0816, 5.0816, 1.7143, 1.7143, 1.7143, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 5.898, 5.898, 5.898, 1.5102, 1.5102, 1.5102, 2.5306, 2.5306, 2.5306, 4.1633, 4.1633, 4.1633, 1.2041, 1.2041, 1.2041, 2.6327, 2.6327, 2.6327, 5.6939, 5.6939, 5.6939, 4.5714, 4.5714, 4.5714, 3.8571, 3.8571, 3.8571, 4.9796, 4.9796, 4.9796, 4.7755, 4.7755, 4.7755, 2.4286, 2.4286, 2.4286, 1, 1, 1, 4.8776, 4.8776, 4.8776, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 3.0408, 3.0408, 3.0408, 4.4694, 4.4694, 4.4694, 4.6735, 4.6735, 4.6735, 1.6122, 1.6122, 1.6122, 2.2245, 2.2245, 2.2245, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 2.0204, 2.0204, 2.0204, 4.0612, 4.0612, 4.0612), SV5 = c(0.198, 0.198, 0.198, 0.2592, 0.2592, 0.2592, 0.2184, 0.2184, 0.2184, 0.1857, 0.1857, 0.1857, 0.1816, 0.1816, 0.1816, 0.1898, 0.1898, 0.1898, 0.1, 0.1, 0.1, 0.2714, 0.2714, 0.2714, 0.1327, 0.1327, 0.1327, 0.2143, 0.2143, 0.2143, 0.1612, 0.1612, 0.1612, 0.1041, 0.1041, 0.1041, 0.2347, 0.2347, 0.2347, 0.1694, 0.1694, 0.1694, 0.1245, 0.1245, 0.1245, 0.1408, 0.1408, 0.1408, 0.2224, 0.2224, 0.2224, 0.3, 0.3, 0.3, 0.2918, 0.2918, 0.2918, 0.2878, 0.2878, 0.2878, 0.1082, 0.1082, 0.1082, 0.2755, 0.2755, 0.2755, 0.2388, 0.2388, 0.2388, 0.1776, 0.1776, 0.1776, 0.2551, 0.2551, 0.2551, 0.1653, 0.1653, 0.1653, 0.1939, 0.1939, 0.1939, 0.1367, 0.1367, 0.1367, 0.2796, 0.2796, 0.2796, 0.2306, 0.2306, 0.2306, 0.1735, 0.1735, 0.1735, 0.2265, 0.2265, 0.2265, 0.2061, 0.2061, 0.2061, 0.2429, 0.2429, 0.2429, 0.1204, 0.1204, 0.1204, 0.251, 0.251, 0.251, 0.1449, 0.1449, 0.1449, 0.202, 0.202, 0.202, 0.2959, 0.2959, 0.2959, 0.1163, 0.1163, 0.1163, 0.1286, 0.1286, 0.1286, 0.1122, 0.1122, 0.1122, 0.2633, 0.2633, 0.2633, 0.149, 0.149, 0.149, 0.2837, 0.2837, 0.2837, 0.2673, 0.2673, 0.2673, 0.2469, 0.2469, 0.2469, 0.2102, 0.2102, 0.2102, 0.1531, 0.1531, 0.1531, 0.1571, 0.1571, 0.1571), SV6 = c(90.2041, 90.2041, 90.2041, 69.7959, 69.7959, 69.7959, 83.6735, 83.6735, 83.6735, 82.0408, 82.0408, 82.0408, 88.5714, 88.5714, 88.5714, 68.9796, 68.9796, 68.9796, 80.4082, 80.4082, 80.4082, 62.449, 62.449, 62.449, 96.7347, 96.7347, 96.7347, 75.5102, 75.5102, 75.5102, 97.551, 97.551, 97.551, 73.8776, 73.8776, 73.8776, 77.1429, 77.1429, 77.1429, 98.3673, 98.3673, 98.3673, 76.3265, 76.3265, 76.3265, 74.6939, 74.6939, 74.6939, 61.6327, 61.6327, 61.6327, 91.8367, 91.8367, 91.8367, 100, 100, 100, 68.1633, 68.1633, 68.1633, 73.0612, 73.0612, 73.0612, 82.8571, 82.8571, 82.8571, 63.2653, 63.2653, 63.2653, 81.2245, 81.2245, 81.2245, 95.9184, 95.9184, 95.9184, 86.9388, 86.9388, 86.9388, 94.2857, 94.2857, 94.2857, 71.4286, 71.4286, 71.4286, 60, 60, 60, 89.3878, 89.3878, 89.3878, 86.1224, 86.1224, 86.1224, 92.6531, 92.6531, 92.6531, 65.7143, 65.7143, 65.7143, 87.7551, 87.7551, 87.7551, 84.4898, 84.4898, 84.4898, 60.8163, 60.8163, 60.8163, 79.5918, 79.5918, 79.5918, 64.0816, 64.0816, 64.0816, 99.1837, 99.1837, 99.1837, 85.3061, 85.3061, 85.3061, 66.5306, 66.5306, 66.5306, 64.898, 64.898, 64.898, 95.102, 95.102, 95.102, 91.0204, 91.0204, 91.0204, 67.3469, 67.3469, 67.3469, 77.9592, 77.9592, 77.9592, 72.2449, 72.2449, 72.2449, 70.6122, 70.6122, 70.6122, 93.4694, 93.4694, 93.4694, 78.7755, 78.7755, 78.7755), SV7 = c(108.1633, 108.1633, 108.1633, 100, 100, 100, 197.9592, 197.9592, 197.9592, 136.7347, 136.7347, 136.7347, 230.6122, 230.6122, 230.6122, 218.3673, 218.3673, 218.3673, 263.2653, 263.2653, 263.2653, 144.898, 144.898, 144.898, 234.6939, 234.6939, 234.6939, 173.4694, 173.4694, 173.4694, 267.3469, 267.3469, 267.3469, 214.2857, 214.2857, 214.2857, 222.449, 222.449, 222.449, 271.4286, 271.4286, 271.4286, 157.1429, 157.1429, 157.1429, 140.8163, 140.8163, 140.8163, 153.0612, 153.0612, 153.0612, 148.9796, 148.9796, 148.9796, 255.102, 255.102, 255.102, 169.3878, 169.3878, 169.3878, 226.5306, 226.5306, 226.5306, 279.5918, 279.5918, 279.5918, 295.9184, 295.9184, 295.9184, 202.0408, 202.0408, 202.0408, 116.3265, 116.3265, 116.3265, 165.3061, 165.3061, 165.3061, 259.1837, 259.1837, 259.1837, 291.8367, 291.8367, 291.8367, 206.1224, 206.1224, 206.1224, 120.4082, 120.4082, 120.4082, 283.6735, 283.6735, 283.6735, 300, 300, 300, 112.2449, 112.2449, 112.2449, 287.7551, 287.7551, 287.7551, 161.2245, 161.2245, 161.2245, 251.0204, 251.0204, 251.0204, 246.9388, 246.9388, 246.9388, 177.551, 177.551, 177.551, 124.4898, 124.4898, 124.4898, 242.8571, 242.8571, 242.8571, 210.2041, 210.2041, 210.2041, 189.7959, 189.7959, 189.7959, 185.7143, 185.7143, 185.7143, 238.7755, 238.7755, 238.7755, 128.5714, 128.5714, 128.5714, 193.8776, 193.8776, 193.8776, 181.6327, 181.6327, 181.6327, 104.0816, 104.0816, 104.0816, 132.6531, 132.6531, 132.6531, 275.5102, 275.5102, 275.5102 )), name = "Pacioni_et_al_ST_LHS_GeneDiv", level = 2, method = "g", crit = "aic", confsetsize = 30, plotty = FALSE, report = FALSE, fitfunction = function (formula, data, subset, na.action, weights, offset, link = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"), link.phi = NULL, type = c("ML", "BC", "BR"), control = betareg.control(...), model = TRUE, y = TRUE, x = FALSE, ...) { cl <- match.call() if (missing(data)) data <- environment(formula) mf <- match.call(expand.dots = FALSE) m <- match(c("formula", "data", "subset", "na.action", "weights", "offset"), names(mf), 0L) mf <- mf[c(1L, m)] mf$drop.unused.levels <- TRUE oformula <- as.formula(formula) formula <- as.Formula(formula) if (length(formula)[2L] < 2L) { formula <- as.Formula(formula(formula), ~1) simple_formula <- TRUE } else { if (length(formula)[2L] > 2L) { formula <- Formula(formula(formula, rhs = 1:2)) warning("formula must not have more than two RHS parts") } simple_formula <- FALSE } mf$formula <- formula mf[[1L]] <- as.name("model.frame") mf <- eval(mf, parent.frame()) mt <- terms(formula, data = data) mtX <- terms(formula, data = data, rhs = 1L) mtZ <- delete.response(terms(formula, data = data, rhs = 2L)) Y <- model.response(mf, "numeric") X <- model.matrix(mtX, mf) Z <- model.matrix(mtZ, mf) if (length(Y) < 1) stop("empty model") if (!(min(Y) > 0 & max(Y) < 1)) stop("invalid dependent variable, all observations must be in (0, 1)") n <- length(Y) type <- match.arg(type) if (is.character(link)) link <- match.arg(link) if (is.null(link.phi)) link.phi <- if (simple_formula) "identity" else "log" if (is.character(link.phi)) link.phi <- match.arg(link.phi, c("identity", "log", "sqrt")) weights <- model.weights(mf) if (is.null(weights)) weights <- 1 if (length(weights) == 1) weights <- rep.int(weights, n) weights <- as.vector(weights) names(weights) <- rownames(mf) expand_offset <- function(offset) { if (is.null(offset)) offset <- 0 if (length(offset) == 1) offset <- rep.int(offset, n) as.vector(offset) } offsetX <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 1L, terms = TRUE))) offsetZ <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 2L, terms = TRUE))) if (!is.null(cl$offset)) offsetX <- offsetX + expand_offset(mf[, "(offset)"]) offset <- list(mean = offsetX, precision = offsetZ) rval <- betareg.fit(X, Y, Z, weights, offset, link, link.phi, type, control) rval$call <- cl rval$formula <- oformula rval$terms <- list(mean = mtX, precision = mtZ, full = mt) rval$levels <- list(mean = .getXlevels(mtX, mf), precision = .getXlevels(mtZ, mf), full = .getXlevels(mt, mf)) rval$contrasts <- list(mean = attr(X, "contrasts"), precision = attr(Z, "contrasts")) if (model) rval$model <- mf if (y) rval$y <- Y if (x) rval$x <- list(mean = X, precision = Z) class(rval) <- "betareg" return(rval) }, link = "cloglog", na.action = function (object, ...) UseMethod("na.omit"), xr = c("SV1", "SV2", "SV3"), exclude = character(0)) --- call from argument --- fitfunction == "glm" && !beber$converged --- R stacktrace --- where 1: glmulti(y = "GeneDiv", data = list(Population = c("Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1"), Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 37L, 37L, 37L, 38L, 38L, 38L, 39L, 39L, 39L, 40L, 40L, 40L, 41L, 41L, 41L, 42L, 42L, 42L, 43L, 43L, 43L, 44L, 44L, 44L, 45L, 45L, 45L, 46L, 46L, 46L, 47L, 47L, 47L, 48L, 48L, 48L, 49L, 49L, 49L, 50L, 50L, 50L), Iteration = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3), YrExt = c(8, 12, 13, NA, NA, NA, NA, NA, NA, 7, 5, 4, 19, 19, 32, 11, 13, 15, 79, 54, 83, 70, 24, 23, NA, NA, NA, 32, 34, 99, NA, NA, NA, NA, NA, NA, 33, 36, 24, NA, NA, NA, NA, NA, NA, 11, 8, 11, NA, NA, NA, 12, 4, 6, 9, 9, 10, 9, 9, 12, NA, NA, NA, NA, NA, NA, 36, 19, 30, NA, 101, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, 18, 13, NA, NA, NA, 15, 24, 21, 7, 10, 10, NA, NA, NA, 29, 24, 22, NA, NA, NA, 31, 55, 20, 33, 39, 35, 48, 50, 30, NA, NA, NA, 109, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), N = c(0, 0, 0, 1384, 1514, 605, 1364, 1366, 1108, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 13, 3, 18, 0, 0, 382, 722, 386, 0, 0, 15, 785, 814, 809, 1253, 1330, 1290, 0, 0, 0, 557, 588, 527, 385, 552, 580, 0, 0, 0, 1166, 1057, 1098, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1106, 1271, 1544, 538, 587, 541, 0, 0, 0, 88, 12, 232, 1087, 1126, 1218, 438, 390, 418, 465, 465, 437, 464, 244, 353, 408, 468, 419, 461, 291, 79, 930, 1010, 764, 663, 580, 678, 781, 796, 847, 476, 577, 603, 355, 187, 879, 0, 0, 0, 982, 996, 884, 0, 0, 0, 0, 0, 0, 1466, 1429, 1464, 0, 0, 0, 755, 731, 776, 0, 0, 0, 0, 0, 10, 0, 0, 0, 1243, 1136, 1216, 23, 52, 379, 213, 183, 81, 682, 681, 690, 1197, 1036, 993), GeneDiv = c(NA, NA, NA, 0.9605, 0.9372, 0.8284, 0.9883, 0.9839, 0.9823, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9339, 0.9538, 0.9679, NA, NA, NA, 0.9674, 0.9658, 0.971, 0.9864, 0.9845, 0.9861, NA, NA, NA, 0.9709, 0.9736, 0.9732, 0.9575, 0.9549, 0.9635, NA, NA, NA, 0.9756, 0.9755, 0.9763, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9642, 0.9636, 0.9632, 0.9716, 0.9713, 0.9664, NA, NA, NA, 0.8917, NA, 0.9211, 0.9744, 0.9703, 0.9742, 0.9634, 0.958, 0.9211, 0.9588, 0.9734, 0.9556, 0.9707, 0.9585, 0.9744, 0.9528, 0.9499, 0.9727, 0.9291, 0.8715, 0.9101, 0.983, 0.9845, 0.9861, 0.9808, 0.9728, 0.9803, 0.9715, 0.9645, 0.9447, 0.9742, 0.9751, 0.9792, 0.9282, 0.9366, 0.9445, NA, NA, NA, 0.9855, 0.9838, 0.9837, NA, NA, NA, NA, NA, NA, 0.9883, 0.988, 0.9882, NA, NA, NA, 0.9612, 0.9546, 0.9663, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9709, 0.9795, 0.9774, NA, 0.86, 0.9333, 0.9194, 0.8876, 0.8112, 0.9502, 0.955, 0.9524, 0.9884, 0.9887, 0.9875), Inbreed = c(NA, NA, NA, 0.0376, 0.0707, 0.1835, 0.011, 0.0205, 0.0162, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0628, 0.0402, 0.0181, NA, NA, NA, 0.0217, 0.0319, 0.0334, 0.016, 0.018, 0.0116, NA, NA, NA, 0.0215, 0.0221, 0.0285, 0.0286, 0.0489, 0.0362, NA, NA, NA, 0.0232, 0.0237, 0.0246, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0407, 0.0393, 0.0298, 0.0353, 0.0187, 0.0314, NA, NA, NA, 0.0909, NA, 0.0776, 0.0313, 0.0284, 0.0263, 0.0137, 0.0359, 0.0622, 0.0409, 0.0129, 0.0526, 0.0302, 0.0492, 0.0283, 0.0515, 0.0769, 0.0167, 0.0651, 0.1375, 0.1013, 0.0183, 0.0149, 0.0196, 0.0226, 0.0276, 0.0206, 0.032, 0.0226, 0.0626, 0.0336, 0.0191, 0.0116, 0.062, 0.0802, 0.0478, NA, NA, NA, 0.0102, 0.005, 0.0147, NA, NA, NA, NA, NA, NA, 0.0109, 0.014, 0.0075, NA, NA, NA, 0.0477, 0.0451, 0.0245, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0241, 0.0194, 0.0214, NA, 0.0962, 0.058, 0.0704, 0.1475, 0.2222, 0.0469, 0.0426, 0.0348, 0.0109, 0.0068, 0.0111), Alleles = c(NA, NA, NA, 51, 31, 12, 146, 113, 119, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, 42, 46, NA, NA, NA, 62, 64, 71, 127, 125, 124, NA, NA, NA, 67, 68, 63, 39, 49, 50, NA, NA, NA, 77, 74, 80, NA, NA, NA, NA, NA, NA, NA, NA, NA, 48, 47, 59, 65, 55, 50, NA, NA, NA, 11, NA, 23, 69, 68, 62, 42, 41, 29, 42, 60, 47, 55, 38, 61, 47, 44, 61, 23, 14, 16, 112, 118, 124, 87, 74, 88, 58, 46, 41, 74, 73, 81, 34, 24, 32, NA, NA, NA, 118, 116, 121, NA, NA, NA, NA, NA, NA, 149, 154, 160, NA, NA, NA, 49, 34, 61, NA, NA, NA, NA, NA, NA, NA, NA, NA, 61, 89, 80, NA, 10, 26, 21, 21, 13, 38, 40, 39, 157, 156, 134 ), SV1 = c(1540.8163, 1540.8163, 1540.8163, 1755.102, 1755.102, 1755.102, 1571.4286, 1571.4286, 1571.4286, 1204.0816, 1204.0816, 1204.0816, 744.898, 744.898, 744.898, 989.7959, 989.7959, 989.7959, 1602.0408, 1602.0408, 1602.0408, 1387.7551, 1387.7551, 1387.7551, 1663.2653, 1663.2653, 1663.2653, 1938.7755, 1938.7755, 1938.7755, 897.9592, 897.9592, 897.9592, 1265.3061, 1265.3061, 1265.3061, 1479.5918, 1479.5918, 1479.5918, 591.8367, 591.8367, 591.8367, 1785.7143, 1785.7143, 1785.7143, 1020.4082, 1020.4082, 1020.4082, 1173.4694, 1173.4694, 1173.4694, 2000, 2000, 2000, 1081.6327, 1081.6327, 1081.6327, 1969.3878, 1969.3878, 1969.3878, 1816.3265, 1816.3265, 1816.3265, 653.0612, 653.0612, 653.0612, 775.5102, 775.5102, 775.5102, 1877.551, 1877.551, 1877.551, 1295.9184, 1295.9184, 1295.9184, 561.2245, 561.2245, 561.2245, 530.6122, 530.6122, 530.6122, 1357.1429, 1357.1429, 1357.1429, 500, 500, 500, 714.2857, 714.2857, 714.2857, 959.1837, 959.1837, 959.1837, 683.6735, 683.6735, 683.6735, 867.3469, 867.3469, 867.3469, 622.449, 622.449, 622.449, 1908.1633, 1908.1633, 1908.1633, 1142.8571, 1142.8571, 1142.8571, 1051.0204, 1051.0204, 1051.0204, 1112.2449, 1112.2449, 1112.2449, 1693.8776, 1693.8776, 1693.8776, 1418.3673, 1418.3673, 1418.3673, 1846.9388, 1846.9388, 1846.9388, 836.7347, 836.7347, 836.7347, 1724.4898, 1724.4898, 1724.4898, 1510.2041, 1510.2041, 1510.2041, 1632.6531, 1632.6531, 1632.6531, 1326.5306, 1326.5306, 1326.5306, 1448.9796, 1448.9796, 1448.9796, 928.5714, 928.5714, 928.5714, 806.1224, 806.1224, 806.1224, 1234.6939, 1234.6939, 1234.6939), SV2 = c(4.5714, 4.5714, 4.5714, 5.0816, 5.0816, 5.0816, 1.4082, 1.4082, 1.4082, 5.898, 5.898, 5.898, 5.2857, 5.2857, 5.2857, 4.7755, 4.7755, 4.7755, 3.0408, 3.0408, 3.0408, 1.8163, 1.8163, 1.8163, 4.1633, 4.1633, 4.1633, 3.8571, 3.8571, 3.8571, 4.8776, 4.8776, 4.8776, 1.7143, 1.7143, 1.7143, 3.7551, 3.7551, 3.7551, 2.5306, 2.5306, 2.5306, 1.9184, 1.9184, 1.9184, 4.6735, 4.6735, 4.6735, 2.0204, 2.0204, 2.0204, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 3.551, 3.551, 3.551, 5.3878, 5.3878, 5.3878, 4.2653, 4.2653, 4.2653, 6, 6, 6, 4.4694, 4.4694, 4.4694, 3.3469, 3.3469, 3.3469, 3.2449, 3.2449, 3.2449, 4.0612, 4.0612, 4.0612, 2.4286, 2.4286, 2.4286, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 1.102, 1.102, 1.102, 2.2245, 2.2245, 2.2245, 2.8367, 2.8367, 2.8367, 1.6122, 1.6122, 1.6122, 5.5918, 5.5918, 5.5918, 2.9388, 2.9388, 2.9388, 1.2041, 1.2041, 1.2041, 5.6939, 5.6939, 5.6939, 3.9592, 3.9592, 3.9592, 1.3061, 1.3061, 1.3061, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 2.7347, 2.7347, 2.7347, 1.5102, 1.5102, 1.5102, 2.6327, 2.6327, 2.6327, 3.449, 3.449, 3.449, 3.6531, 3.6531, 3.6531, 2.3265, 2.3265, 2.3265, 5.4898, 5.4898, 5.4898, 1, 1, 1), SV3 = c(3.8571, 3.8571, 3.8571, 1.5102, 1.5102, 1.5102, 4.1633, 4.1633, 4.1633, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 5.1837, 5.1837, 5.1837, 4.6735, 4.6735, 4.6735, 5.3878, 5.3878, 5.3878, 3.1429, 3.1429, 3.1429, 3.551, 3.551, 3.551, 1.6122, 1.6122, 1.6122, 2.3265, 2.3265, 2.3265, 3.9592, 3.9592, 3.9592, 2.5306, 2.5306, 2.5306, 4.5714, 4.5714, 4.5714, 4.7755, 4.7755, 4.7755, 3.7551, 3.7551, 3.7551, 4.8776, 4.8776, 4.8776, 5.6939, 5.6939, 5.6939, 6, 6, 6, 1.3061, 1.3061, 1.3061, 1.4082, 1.4082, 1.4082, 3.2449, 3.2449, 3.2449, 2.9388, 2.9388, 2.9388, 2.0204, 2.0204, 2.0204, 2.8367, 2.8367, 2.8367, 1.7143, 1.7143, 1.7143, 4.4694, 4.4694, 4.4694, 1.9184, 1.9184, 1.9184, 2.2245, 2.2245, 2.2245, 1.8163, 1.8163, 1.8163, 1.2041, 1.2041, 1.2041, 2.7347, 2.7347, 2.7347, 3.3469, 3.3469, 3.3469, 1, 1, 1, 5.898, 5.898, 5.898, 4.3673, 4.3673, 4.3673, 3.6531, 3.6531, 3.6531, 5.2857, 5.2857, 5.2857, 2.1224, 2.1224, 2.1224, 5.4898, 5.4898, 5.4898, 2.4286, 2.4286, 2.4286, 5.0816, 5.0816, 5.0816, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 2.6327, 2.6327, 2.6327, 3.0408, 3.0408, 3.0408, 4.2653, 4.2653, 4.2653, 1.102, 1.102, 1.102, 4.0612, 4.0612, 4.0612), SV4 = c(5.2857, 5.2857, 5.2857, 1.102, 1.102, 1.102, 3.551, 3.551, 3.551, 2.8367, 2.8367, 2.8367, 3.3469, 3.3469, 3.3469, 2.9388, 2.9388, 2.9388, 1.3061, 1.3061, 1.3061, 5.4898, 5.4898, 5.4898, 1.4082, 1.4082, 1.4082, 2.7347, 2.7347, 2.7347, 1.8163, 1.8163, 1.8163, 3.6531, 3.6531, 3.6531, 4.2653, 4.2653, 4.2653, 2.3265, 2.3265, 2.3265, 3.7551, 3.7551, 3.7551, 3.9592, 3.9592, 3.9592, 1.9184, 1.9184, 1.9184, 5.7959, 5.7959, 5.7959, 6, 6, 6, 5.3878, 5.3878, 5.3878, 3.2449, 3.2449, 3.2449, 5.0816, 5.0816, 5.0816, 1.7143, 1.7143, 1.7143, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 5.898, 5.898, 5.898, 1.5102, 1.5102, 1.5102, 2.5306, 2.5306, 2.5306, 4.1633, 4.1633, 4.1633, 1.2041, 1.2041, 1.2041, 2.6327, 2.6327, 2.6327, 5.6939, 5.6939, 5.6939, 4.5714, 4.5714, 4.5714, 3.8571, 3.8571, 3.8571, 4.9796, 4.9796, 4.9796, 4.7755, 4.7755, 4.7755, 2.4286, 2.4286, 2.4286, 1, 1, 1, 4.8776, 4.8776, 4.8776, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 3.0408, 3.0408, 3.0408, 4.4694, 4.4694, 4.4694, 4.6735, 4.6735, 4.6735, 1.6122, 1.6122, 1.6122, 2.2245, 2.2245, 2.2245, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 2.0204, 2.0204, 2.0204, 4.0612, 4.0612, 4.0612), SV5 = c(0.198, 0.198, 0.198, 0.2592, 0.2592, 0.2592, 0.2184, 0.2184, 0.2184, 0.1857, 0.1857, 0.1857, 0.1816, 0.1816, 0.1816, 0.1898, 0.1898, 0.1898, 0.1, 0.1, 0.1, 0.2714, 0.2714, 0.2714, 0.1327, 0.1327, 0.1327, 0.2143, 0.2143, 0.2143, 0.1612, 0.1612, 0.1612, 0.1041, 0.1041, 0.1041, 0.2347, 0.2347, 0.2347, 0.1694, 0.1694, 0.1694, 0.1245, 0.1245, 0.1245, 0.1408, 0.1408, 0.1408, 0.2224, 0.2224, 0.2224, 0.3, 0.3, 0.3, 0.2918, 0.2918, 0.2918, 0.2878, 0.2878, 0.2878, 0.1082, 0.1082, 0.1082, 0.2755, 0.2755, 0.2755, 0.2388, 0.2388, 0.2388, 0.1776, 0.1776, 0.1776, 0.2551, 0.2551, 0.2551, 0.1653, 0.1653, 0.1653, 0.1939, 0.1939, 0.1939, 0.1367, 0.1367, 0.1367, 0.2796, 0.2796, 0.2796, 0.2306, 0.2306, 0.2306, 0.1735, 0.1735, 0.1735, 0.2265, 0.2265, 0.2265, 0.2061, 0.2061, 0.2061, 0.2429, 0.2429, 0.2429, 0.1204, 0.1204, 0.1204, 0.251, 0.251, 0.251, 0.1449, 0.1449, 0.1449, 0.202, 0.202, 0.202, 0.2959, 0.2959, 0.2959, 0.1163, 0.1163, 0.1163, 0.1286, 0.1286, 0.1286, 0.1122, 0.1122, 0.1122, 0.2633, 0.2633, 0.2633, 0.149, 0.149, 0.149, 0.2837, 0.2837, 0.2837, 0.2673, 0.2673, 0.2673, 0.2469, 0.2469, 0.2469, 0.2102, 0.2102, 0.2102, 0.1531, 0.1531, 0.1531, 0.1571, 0.1571, 0.1571), SV6 = c(90.2041, 90.2041, 90.2041, 69.7959, 69.7959, 69.7959, 83.6735, 83.6735, 83.6735, 82.0408, 82.0408, 82.0408, 88.5714, 88.5714, 88.5714, 68.9796, 68.9796, 68.9796, 80.4082, 80.4082, 80.4082, 62.449, 62.449, 62.449, 96.7347, 96.7347, 96.7347, 75.5102, 75.5102, 75.5102, 97.551, 97.551, 97.551, 73.8776, 73.8776, 73.8776, 77.1429, 77.1429, 77.1429, 98.3673, 98.3673, 98.3673, 76.3265, 76.3265, 76.3265, 74.6939, 74.6939, 74.6939, 61.6327, 61.6327, 61.6327, 91.8367, 91.8367, 91.8367, 100, 100, 100, 68.1633, 68.1633, 68.1633, 73.0612, 73.0612, 73.0612, 82.8571, 82.8571, 82.8571, 63.2653, 63.2653, 63.2653, 81.2245, 81.2245, 81.2245, 95.9184, 95.9184, 95.9184, 86.9388, 86.9388, 86.9388, 94.2857, 94.2857, 94.2857, 71.4286, 71.4286, 71.4286, 60, 60, 60, 89.3878, 89.3878, 89.3878, 86.1224, 86.1224, 86.1224, 92.6531, 92.6531, 92.6531, 65.7143, 65.7143, 65.7143, 87.7551, 87.7551, 87.7551, 84.4898, 84.4898, 84.4898, 60.8163, 60.8163, 60.8163, 79.5918, 79.5918, 79.5918, 64.0816, 64.0816, 64.0816, 99.1837, 99.1837, 99.1837, 85.3061, 85.3061, 85.3061, 66.5306, 66.5306, 66.5306, 64.898, 64.898, 64.898, 95.102, 95.102, 95.102, 91.0204, 91.0204, 91.0204, 67.3469, 67.3469, 67.3469, 77.9592, 77.9592, 77.9592, 72.2449, 72.2449, 72.2449, 70.6122, 70.6122, 70.6122, 93.4694, 93.4694, 93.4694, 78.7755, 78.7755, 78.7755), SV7 = c(108.1633, 108.1633, 108.1633, 100, 100, 100, 197.9592, 197.9592, 197.9592, 136.7347, 136.7347, 136.7347, 230.6122, 230.6122, 230.6122, 218.3673, 218.3673, 218.3673, 263.2653, 263.2653, 263.2653, 144.898, 144.898, 144.898, 234.6939, 234.6939, 234.6939, 173.4694, 173.4694, 173.4694, 267.3469, 267.3469, 267.3469, 214.2857, 214.2857, 214.2857, 222.449, 222.449, 222.449, 271.4286, 271.4286, 271.4286, 157.1429, 157.1429, 157.1429, 140.8163, 140.8163, 140.8163, 153.0612, 153.0612, 153.0612, 148.9796, 148.9796, 148.9796, 255.102, 255.102, 255.102, 169.3878, 169.3878, 169.3878, 226.5306, 226.5306, 226.5306, 279.5918, 279.5918, 279.5918, 295.9184, 295.9184, 295.9184, 202.0408, 202.0408, 202.0408, 116.3265, 116.3265, 116.3265, 165.3061, 165.3061, 165.3061, 259.1837, 259.1837, 259.1837, 291.8367, 291.8367, 291.8367, 206.1224, 206.1224, 206.1224, 120.4082, 120.4082, 120.4082, 283.6735, 283.6735, 283.6735, 300, 300, 300, 112.2449, 112.2449, 112.2449, 287.7551, 287.7551, 287.7551, 161.2245, 161.2245, 161.2245, 251.0204, 251.0204, 251.0204, 246.9388, 246.9388, 246.9388, 177.551, 177.551, 177.551, 124.4898, 124.4898, 124.4898, 242.8571, 242.8571, 242.8571, 210.2041, 210.2041, 210.2041, 189.7959, 189.7959, 189.7959, 185.7143, 185.7143, 185.7143, 238.7755, 238.7755, 238.7755, 128.5714, 128.5714, 128.5714, 193.8776, 193.8776, 193.8776, 181.6327, 181.6327, 181.6327, 104.0816, 104.0816, 104.0816, 132.6531, 132.6531, 132.6531, 275.5102, 275.5102, 275.5102 )), name = "Pacioni_et_al_ST_LHS_GeneDiv", level = 2, method = "g", crit = "aic", confsetsize = 30, plotty = FALSE, report = FALSE, fitfunction = function (formula, data, subset, na.action, weights, offset, link = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"), link.phi = NULL, type = c("ML", "BC", "BR"), control = betareg.control(...), model = TRUE, y = TRUE, x = FALSE, ...) { cl <- match.call() if (missing(data)) data <- environment(formula) mf <- match.call(expand.dots = FALSE) m <- match(c("formula", "data", "subset", "na.action", "weights", "offset"), names(mf), 0L) mf <- mf[c(1L, m)] mf$drop.unused.levels <- TRUE oformula <- as.formula(formula) formula <- as.Formula(formula) if (length(formula)[2L] < 2L) { formula <- as.Formula(formula(formula), ~1) simple_formula <- TRUE } else { if (length(formula)[2L] > 2L) { formula <- Formula(formula(formula, rhs = 1:2)) warning("formula must not have more than two RHS parts") } simple_formula <- FALSE } mf$formula <- formula mf[[1L]] <- as.name("model.frame") mf <- eval(mf, parent.frame()) mt <- terms(formula, data = data) mtX <- terms(formula, data = data, rhs = 1L) mtZ <- delete.response(terms(formula, data = data, rhs = 2L)) Y <- model.response(mf, "numeric") X <- model.matrix(mtX, mf) Z <- model.matrix(mtZ, mf) if (length(Y) < 1) stop("empty model") if (!(min(Y) > 0 & max(Y) < 1)) stop("invalid dependent variable, all observations must be in (0, 1)") n <- length(Y) type <- match.arg(type) if (is.character(link)) link <- match.arg(link) if (is.null(link.phi)) link.phi <- if (simple_formula) "identity" else "log" if (is.character(link.phi)) link.phi <- match.arg(link.phi, c("identity", "log", "sqrt")) weights <- model.weights(mf) if (is.null(weights)) weights <- 1 if (length(weights) == 1) weights <- rep.int(weights, n) weights <- as.vector(weights) names(weights) <- rownames(mf) expand_offset <- function(offset) { if (is.null(offset)) offset <- 0 if (length(offset) == 1) offset <- rep.int(offset, n) as.vector(offset) } offsetX <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 1L, terms = TRUE))) offsetZ <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 2L, terms = TRUE))) if (!is.null(cl$offset)) offsetX <- offsetX + expand_offset(mf[, "(offset)"]) offset <- list(mean = offsetX, precision = offsetZ) rval <- betareg.fit(X, Y, Z, weights, offset, link, link.phi, type, control) rval$call <- cl rval$formula <- oformula rval$terms <- list(mean = mtX, precision = mtZ, full = mt) rval$levels <- list(mean = .getXlevels(mtX, mf), precision = .getXlevels(mtZ, mf), full = .getXlevels(mt, mf)) rval$contrasts <- list(mean = attr(X, "contrasts"), precision = attr(Z, "contrasts")) if (model) rval$model <- mf if (y) rval$y <- Y if (x) rval$x <- list(mean = X, precision = Z) class(rval) <- "betareg" return(rval) }, link = "cloglog", na.action = function (object, ...) UseMethod("na.omit"), xr = c("SV1", "SV2", "SV3"), exclude = character(0)) where 2: glmulti(y = "GeneDiv", data = list(Population = c("Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1"), Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 37L, 37L, 37L, 38L, 38L, 38L, 39L, 39L, 39L, 40L, 40L, 40L, 41L, 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0.2755, 0.2755, 0.2755, 0.2388, 0.2388, 0.2388, 0.1776, 0.1776, 0.1776, 0.2551, 0.2551, 0.2551, 0.1653, 0.1653, 0.1653, 0.1939, 0.1939, 0.1939, 0.1367, 0.1367, 0.1367, 0.2796, 0.2796, 0.2796, 0.2306, 0.2306, 0.2306, 0.1735, 0.1735, 0.1735, 0.2265, 0.2265, 0.2265, 0.2061, 0.2061, 0.2061, 0.2429, 0.2429, 0.2429, 0.1204, 0.1204, 0.1204, 0.251, 0.251, 0.251, 0.1449, 0.1449, 0.1449, 0.202, 0.202, 0.202, 0.2959, 0.2959, 0.2959, 0.1163, 0.1163, 0.1163, 0.1286, 0.1286, 0.1286, 0.1122, 0.1122, 0.1122, 0.2633, 0.2633, 0.2633, 0.149, 0.149, 0.149, 0.2837, 0.2837, 0.2837, 0.2673, 0.2673, 0.2673, 0.2469, 0.2469, 0.2469, 0.2102, 0.2102, 0.2102, 0.1531, 0.1531, 0.1531, 0.1571, 0.1571, 0.1571), SV6 = c(90.2041, 90.2041, 90.2041, 69.7959, 69.7959, 69.7959, 83.6735, 83.6735, 83.6735, 82.0408, 82.0408, 82.0408, 88.5714, 88.5714, 88.5714, 68.9796, 68.9796, 68.9796, 80.4082, 80.4082, 80.4082, 62.449, 62.449, 62.449, 96.7347, 96.7347, 96.7347, 75.5102, 75.5102, 75.5102, 97.551, 97.551, 97.551, 73.8776, 73.8776, 73.8776, 77.1429, 77.1429, 77.1429, 98.3673, 98.3673, 98.3673, 76.3265, 76.3265, 76.3265, 74.6939, 74.6939, 74.6939, 61.6327, 61.6327, 61.6327, 91.8367, 91.8367, 91.8367, 100, 100, 100, 68.1633, 68.1633, 68.1633, 73.0612, 73.0612, 73.0612, 82.8571, 82.8571, 82.8571, 63.2653, 63.2653, 63.2653, 81.2245, 81.2245, 81.2245, 95.9184, 95.9184, 95.9184, 86.9388, 86.9388, 86.9388, 94.2857, 94.2857, 94.2857, 71.4286, 71.4286, 71.4286, 60, 60, 60, 89.3878, 89.3878, 89.3878, 86.1224, 86.1224, 86.1224, 92.6531, 92.6531, 92.6531, 65.7143, 65.7143, 65.7143, 87.7551, 87.7551, 87.7551, 84.4898, 84.4898, 84.4898, 60.8163, 60.8163, 60.8163, 79.5918, 79.5918, 79.5918, 64.0816, 64.0816, 64.0816, 99.1837, 99.1837, 99.1837, 85.3061, 85.3061, 85.3061, 66.5306, 66.5306, 66.5306, 64.898, 64.898, 64.898, 95.102, 95.102, 95.102, 91.0204, 91.0204, 91.0204, 67.3469, 67.3469, 67.3469, 77.9592, 77.9592, 77.9592, 72.2449, 72.2449, 72.2449, 70.6122, 70.6122, 70.6122, 93.4694, 93.4694, 93.4694, 78.7755, 78.7755, 78.7755), SV7 = c(108.1633, 108.1633, 108.1633, 100, 100, 100, 197.9592, 197.9592, 197.9592, 136.7347, 136.7347, 136.7347, 230.6122, 230.6122, 230.6122, 218.3673, 218.3673, 218.3673, 263.2653, 263.2653, 263.2653, 144.898, 144.898, 144.898, 234.6939, 234.6939, 234.6939, 173.4694, 173.4694, 173.4694, 267.3469, 267.3469, 267.3469, 214.2857, 214.2857, 214.2857, 222.449, 222.449, 222.449, 271.4286, 271.4286, 271.4286, 157.1429, 157.1429, 157.1429, 140.8163, 140.8163, 140.8163, 153.0612, 153.0612, 153.0612, 148.9796, 148.9796, 148.9796, 255.102, 255.102, 255.102, 169.3878, 169.3878, 169.3878, 226.5306, 226.5306, 226.5306, 279.5918, 279.5918, 279.5918, 295.9184, 295.9184, 295.9184, 202.0408, 202.0408, 202.0408, 116.3265, 116.3265, 116.3265, 165.3061, 165.3061, 165.3061, 259.1837, 259.1837, 259.1837, 291.8367, 291.8367, 291.8367, 206.1224, 206.1224, 206.1224, 120.4082, 120.4082, 120.4082, 283.6735, 283.6735, 283.6735, 300, 300, 300, 112.2449, 112.2449, 112.2449, 287.7551, 287.7551, 287.7551, 161.2245, 161.2245, 161.2245, 251.0204, 251.0204, 251.0204, 246.9388, 246.9388, 246.9388, 177.551, 177.551, 177.551, 124.4898, 124.4898, 124.4898, 242.8571, 242.8571, 242.8571, 210.2041, 210.2041, 210.2041, 189.7959, 189.7959, 189.7959, 185.7143, 185.7143, 185.7143, 238.7755, 238.7755, 238.7755, 128.5714, 128.5714, 128.5714, 193.8776, 193.8776, 193.8776, 181.6327, 181.6327, 181.6327, 104.0816, 104.0816, 104.0816, 132.6531, 132.6531, 132.6531, 275.5102, 275.5102, 275.5102 )), name = "Pacioni_et_al_ST_LHS_GeneDiv", level = 2, method = "g", crit = "aic", confsetsize = 30, plotty = FALSE, report = FALSE, fitfunction = function (formula, data, subset, na.action, weights, offset, link = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"), link.phi = NULL, type = c("ML", "BC", "BR"), control = betareg.control(...), model = TRUE, y = TRUE, x = FALSE, ...) { cl <- match.call() if (missing(data)) data <- environment(formula) mf <- match.call(expand.dots = FALSE) m <- match(c("formula", "data", "subset", "na.action", "weights", "offset"), names(mf), 0L) mf <- mf[c(1L, m)] mf$drop.unused.levels <- TRUE oformula <- as.formula(formula) formula <- as.Formula(formula) if (length(formula)[2L] < 2L) { formula <- as.Formula(formula(formula), ~1) simple_formula <- TRUE } else { if (length(formula)[2L] > 2L) { formula <- Formula(formula(formula, rhs = 1:2)) warning("formula must not have more than two RHS parts") } simple_formula <- FALSE } mf$formula <- formula mf[[1L]] <- as.name("model.frame") mf <- eval(mf, parent.frame()) mt <- terms(formula, data = data) mtX <- terms(formula, data = data, rhs = 1L) mtZ <- delete.response(terms(formula, data = data, rhs = 2L)) Y <- model.response(mf, "numeric") X <- model.matrix(mtX, mf) Z <- model.matrix(mtZ, mf) if (length(Y) < 1) stop("empty model") if (!(min(Y) > 0 & max(Y) < 1)) stop("invalid dependent variable, all observations must be in (0, 1)") n <- length(Y) type <- match.arg(type) if (is.character(link)) link <- match.arg(link) if (is.null(link.phi)) link.phi <- if (simple_formula) "identity" else "log" if (is.character(link.phi)) link.phi <- match.arg(link.phi, c("identity", "log", "sqrt")) weights <- model.weights(mf) if (is.null(weights)) weights <- 1 if (length(weights) == 1) weights <- rep.int(weights, n) weights <- as.vector(weights) names(weights) <- rownames(mf) expand_offset <- function(offset) { if (is.null(offset)) offset <- 0 if (length(offset) == 1) offset <- rep.int(offset, n) as.vector(offset) } offsetX <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 1L, terms = TRUE))) offsetZ <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 2L, terms = TRUE))) if (!is.null(cl$offset)) offsetX <- offsetX + expand_offset(mf[, "(offset)"]) offset <- list(mean = offsetX, precision = offsetZ) rval <- betareg.fit(X, Y, Z, weights, offset, link, link.phi, type, control) rval$call <- cl rval$formula <- oformula rval$terms <- list(mean = mtX, precision = mtZ, full = mt) rval$levels <- list(mean = .getXlevels(mtX, mf), precision = .getXlevels(mtZ, mf), full = .getXlevels(mt, mf)) rval$contrasts <- list(mean = attr(X, "contrasts"), precision = attr(Z, "contrasts")) if (model) rval$model <- mf if (y) rval$y <- Y if (x) rval$x <- list(mean = X, precision = Z) class(rval) <- "betareg" return(rval) }, link = "cloglog", na.action = function (object, ...) UseMethod("na.omit"), xr = c("SV1", "SV2", "SV3"), exclude = character(0)) where 3: eval(call) where 4: eval(call) where 5: glmulti(GeneDiv ~ SV1 * SV2 * SV3, data = list(Population = c("Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1"), Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 37L, 37L, 37L, 38L, 38L, 38L, 39L, 39L, 39L, 40L, 40L, 40L, 41L, 41L, 41L, 42L, 42L, 42L, 43L, 43L, 43L, 44L, 44L, 44L, 45L, 45L, 45L, 46L, 46L, 46L, 47L, 47L, 47L, 48L, 48L, 48L, 49L, 49L, 49L, 50L, 50L, 50L), Iteration = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3), YrExt = c(8, 12, 13, NA, NA, NA, NA, NA, NA, 7, 5, 4, 19, 19, 32, 11, 13, 15, 79, 54, 83, 70, 24, 23, NA, NA, NA, 32, 34, 99, NA, NA, NA, NA, NA, NA, 33, 36, 24, NA, NA, NA, NA, NA, NA, 11, 8, 11, NA, NA, NA, 12, 4, 6, 9, 9, 10, 9, 9, 12, NA, NA, NA, NA, NA, NA, 36, 19, 30, NA, 101, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, 18, 13, NA, NA, NA, 15, 24, 21, 7, 10, 10, NA, NA, NA, 29, 24, 22, NA, NA, NA, 31, 55, 20, 33, 39, 35, 48, 50, 30, NA, NA, NA, 109, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), N = c(0, 0, 0, 1384, 1514, 605, 1364, 1366, 1108, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 13, 3, 18, 0, 0, 382, 722, 386, 0, 0, 15, 785, 814, 809, 1253, 1330, 1290, 0, 0, 0, 557, 588, 527, 385, 552, 580, 0, 0, 0, 1166, 1057, 1098, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1106, 1271, 1544, 538, 587, 541, 0, 0, 0, 88, 12, 232, 1087, 1126, 1218, 438, 390, 418, 465, 465, 437, 464, 244, 353, 408, 468, 419, 461, 291, 79, 930, 1010, 764, 663, 580, 678, 781, 796, 847, 476, 577, 603, 355, 187, 879, 0, 0, 0, 982, 996, 884, 0, 0, 0, 0, 0, 0, 1466, 1429, 1464, 0, 0, 0, 755, 731, 776, 0, 0, 0, 0, 0, 10, 0, 0, 0, 1243, 1136, 1216, 23, 52, 379, 213, 183, 81, 682, 681, 690, 1197, 1036, 993), GeneDiv = c(NA, NA, NA, 0.9605, 0.9372, 0.8284, 0.9883, 0.9839, 0.9823, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9339, 0.9538, 0.9679, NA, NA, NA, 0.9674, 0.9658, 0.971, 0.9864, 0.9845, 0.9861, NA, NA, NA, 0.9709, 0.9736, 0.9732, 0.9575, 0.9549, 0.9635, NA, NA, NA, 0.9756, 0.9755, 0.9763, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9642, 0.9636, 0.9632, 0.9716, 0.9713, 0.9664, NA, NA, NA, 0.8917, NA, 0.9211, 0.9744, 0.9703, 0.9742, 0.9634, 0.958, 0.9211, 0.9588, 0.9734, 0.9556, 0.9707, 0.9585, 0.9744, 0.9528, 0.9499, 0.9727, 0.9291, 0.8715, 0.9101, 0.983, 0.9845, 0.9861, 0.9808, 0.9728, 0.9803, 0.9715, 0.9645, 0.9447, 0.9742, 0.9751, 0.9792, 0.9282, 0.9366, 0.9445, NA, NA, NA, 0.9855, 0.9838, 0.9837, NA, NA, NA, NA, NA, NA, 0.9883, 0.988, 0.9882, NA, NA, NA, 0.9612, 0.9546, 0.9663, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9709, 0.9795, 0.9774, NA, 0.86, 0.9333, 0.9194, 0.8876, 0.8112, 0.9502, 0.955, 0.9524, 0.9884, 0.9887, 0.9875), Inbreed = c(NA, NA, NA, 0.0376, 0.0707, 0.1835, 0.011, 0.0205, 0.0162, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0628, 0.0402, 0.0181, NA, NA, NA, 0.0217, 0.0319, 0.0334, 0.016, 0.018, 0.0116, NA, NA, NA, 0.0215, 0.0221, 0.0285, 0.0286, 0.0489, 0.0362, NA, NA, NA, 0.0232, 0.0237, 0.0246, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0407, 0.0393, 0.0298, 0.0353, 0.0187, 0.0314, NA, NA, NA, 0.0909, NA, 0.0776, 0.0313, 0.0284, 0.0263, 0.0137, 0.0359, 0.0622, 0.0409, 0.0129, 0.0526, 0.0302, 0.0492, 0.0283, 0.0515, 0.0769, 0.0167, 0.0651, 0.1375, 0.1013, 0.0183, 0.0149, 0.0196, 0.0226, 0.0276, 0.0206, 0.032, 0.0226, 0.0626, 0.0336, 0.0191, 0.0116, 0.062, 0.0802, 0.0478, NA, NA, NA, 0.0102, 0.005, 0.0147, NA, NA, NA, NA, NA, NA, 0.0109, 0.014, 0.0075, NA, NA, NA, 0.0477, 0.0451, 0.0245, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.0241, 0.0194, 0.0214, NA, 0.0962, 0.058, 0.0704, 0.1475, 0.2222, 0.0469, 0.0426, 0.0348, 0.0109, 0.0068, 0.0111), Alleles = c(NA, NA, NA, 51, 31, 12, 146, 113, 119, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, 42, 46, NA, NA, NA, 62, 64, 71, 127, 125, 124, NA, NA, NA, 67, 68, 63, 39, 49, 50, NA, NA, NA, 77, 74, 80, NA, NA, NA, NA, NA, NA, NA, NA, NA, 48, 47, 59, 65, 55, 50, NA, NA, NA, 11, NA, 23, 69, 68, 62, 42, 41, 29, 42, 60, 47, 55, 38, 61, 47, 44, 61, 23, 14, 16, 112, 118, 124, 87, 74, 88, 58, 46, 41, 74, 73, 81, 34, 24, 32, NA, NA, NA, 118, 116, 121, NA, NA, NA, NA, NA, NA, 149, 154, 160, NA, NA, NA, 49, 34, 61, NA, NA, NA, NA, NA, NA, NA, NA, NA, 61, 89, 80, NA, 10, 26, 21, 21, 13, 38, 40, 39, 157, 156, 134 ), SV1 = c(1540.8163, 1540.8163, 1540.8163, 1755.102, 1755.102, 1755.102, 1571.4286, 1571.4286, 1571.4286, 1204.0816, 1204.0816, 1204.0816, 744.898, 744.898, 744.898, 989.7959, 989.7959, 989.7959, 1602.0408, 1602.0408, 1602.0408, 1387.7551, 1387.7551, 1387.7551, 1663.2653, 1663.2653, 1663.2653, 1938.7755, 1938.7755, 1938.7755, 897.9592, 897.9592, 897.9592, 1265.3061, 1265.3061, 1265.3061, 1479.5918, 1479.5918, 1479.5918, 591.8367, 591.8367, 591.8367, 1785.7143, 1785.7143, 1785.7143, 1020.4082, 1020.4082, 1020.4082, 1173.4694, 1173.4694, 1173.4694, 2000, 2000, 2000, 1081.6327, 1081.6327, 1081.6327, 1969.3878, 1969.3878, 1969.3878, 1816.3265, 1816.3265, 1816.3265, 653.0612, 653.0612, 653.0612, 775.5102, 775.5102, 775.5102, 1877.551, 1877.551, 1877.551, 1295.9184, 1295.9184, 1295.9184, 561.2245, 561.2245, 561.2245, 530.6122, 530.6122, 530.6122, 1357.1429, 1357.1429, 1357.1429, 500, 500, 500, 714.2857, 714.2857, 714.2857, 959.1837, 959.1837, 959.1837, 683.6735, 683.6735, 683.6735, 867.3469, 867.3469, 867.3469, 622.449, 622.449, 622.449, 1908.1633, 1908.1633, 1908.1633, 1142.8571, 1142.8571, 1142.8571, 1051.0204, 1051.0204, 1051.0204, 1112.2449, 1112.2449, 1112.2449, 1693.8776, 1693.8776, 1693.8776, 1418.3673, 1418.3673, 1418.3673, 1846.9388, 1846.9388, 1846.9388, 836.7347, 836.7347, 836.7347, 1724.4898, 1724.4898, 1724.4898, 1510.2041, 1510.2041, 1510.2041, 1632.6531, 1632.6531, 1632.6531, 1326.5306, 1326.5306, 1326.5306, 1448.9796, 1448.9796, 1448.9796, 928.5714, 928.5714, 928.5714, 806.1224, 806.1224, 806.1224, 1234.6939, 1234.6939, 1234.6939), SV2 = c(4.5714, 4.5714, 4.5714, 5.0816, 5.0816, 5.0816, 1.4082, 1.4082, 1.4082, 5.898, 5.898, 5.898, 5.2857, 5.2857, 5.2857, 4.7755, 4.7755, 4.7755, 3.0408, 3.0408, 3.0408, 1.8163, 1.8163, 1.8163, 4.1633, 4.1633, 4.1633, 3.8571, 3.8571, 3.8571, 4.8776, 4.8776, 4.8776, 1.7143, 1.7143, 1.7143, 3.7551, 3.7551, 3.7551, 2.5306, 2.5306, 2.5306, 1.9184, 1.9184, 1.9184, 4.6735, 4.6735, 4.6735, 2.0204, 2.0204, 2.0204, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 3.551, 3.551, 3.551, 5.3878, 5.3878, 5.3878, 4.2653, 4.2653, 4.2653, 6, 6, 6, 4.4694, 4.4694, 4.4694, 3.3469, 3.3469, 3.3469, 3.2449, 3.2449, 3.2449, 4.0612, 4.0612, 4.0612, 2.4286, 2.4286, 2.4286, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 1.102, 1.102, 1.102, 2.2245, 2.2245, 2.2245, 2.8367, 2.8367, 2.8367, 1.6122, 1.6122, 1.6122, 5.5918, 5.5918, 5.5918, 2.9388, 2.9388, 2.9388, 1.2041, 1.2041, 1.2041, 5.6939, 5.6939, 5.6939, 3.9592, 3.9592, 3.9592, 1.3061, 1.3061, 1.3061, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 2.7347, 2.7347, 2.7347, 1.5102, 1.5102, 1.5102, 2.6327, 2.6327, 2.6327, 3.449, 3.449, 3.449, 3.6531, 3.6531, 3.6531, 2.3265, 2.3265, 2.3265, 5.4898, 5.4898, 5.4898, 1, 1, 1), SV3 = c(3.8571, 3.8571, 3.8571, 1.5102, 1.5102, 1.5102, 4.1633, 4.1633, 4.1633, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 5.1837, 5.1837, 5.1837, 4.6735, 4.6735, 4.6735, 5.3878, 5.3878, 5.3878, 3.1429, 3.1429, 3.1429, 3.551, 3.551, 3.551, 1.6122, 1.6122, 1.6122, 2.3265, 2.3265, 2.3265, 3.9592, 3.9592, 3.9592, 2.5306, 2.5306, 2.5306, 4.5714, 4.5714, 4.5714, 4.7755, 4.7755, 4.7755, 3.7551, 3.7551, 3.7551, 4.8776, 4.8776, 4.8776, 5.6939, 5.6939, 5.6939, 6, 6, 6, 1.3061, 1.3061, 1.3061, 1.4082, 1.4082, 1.4082, 3.2449, 3.2449, 3.2449, 2.9388, 2.9388, 2.9388, 2.0204, 2.0204, 2.0204, 2.8367, 2.8367, 2.8367, 1.7143, 1.7143, 1.7143, 4.4694, 4.4694, 4.4694, 1.9184, 1.9184, 1.9184, 2.2245, 2.2245, 2.2245, 1.8163, 1.8163, 1.8163, 1.2041, 1.2041, 1.2041, 2.7347, 2.7347, 2.7347, 3.3469, 3.3469, 3.3469, 1, 1, 1, 5.898, 5.898, 5.898, 4.3673, 4.3673, 4.3673, 3.6531, 3.6531, 3.6531, 5.2857, 5.2857, 5.2857, 2.1224, 2.1224, 2.1224, 5.4898, 5.4898, 5.4898, 2.4286, 2.4286, 2.4286, 5.0816, 5.0816, 5.0816, 5.7959, 5.7959, 5.7959, 4.9796, 4.9796, 4.9796, 2.6327, 2.6327, 2.6327, 3.0408, 3.0408, 3.0408, 4.2653, 4.2653, 4.2653, 1.102, 1.102, 1.102, 4.0612, 4.0612, 4.0612), SV4 = c(5.2857, 5.2857, 5.2857, 1.102, 1.102, 1.102, 3.551, 3.551, 3.551, 2.8367, 2.8367, 2.8367, 3.3469, 3.3469, 3.3469, 2.9388, 2.9388, 2.9388, 1.3061, 1.3061, 1.3061, 5.4898, 5.4898, 5.4898, 1.4082, 1.4082, 1.4082, 2.7347, 2.7347, 2.7347, 1.8163, 1.8163, 1.8163, 3.6531, 3.6531, 3.6531, 4.2653, 4.2653, 4.2653, 2.3265, 2.3265, 2.3265, 3.7551, 3.7551, 3.7551, 3.9592, 3.9592, 3.9592, 1.9184, 1.9184, 1.9184, 5.7959, 5.7959, 5.7959, 6, 6, 6, 5.3878, 5.3878, 5.3878, 3.2449, 3.2449, 3.2449, 5.0816, 5.0816, 5.0816, 1.7143, 1.7143, 1.7143, 2.1224, 2.1224, 2.1224, 4.3673, 4.3673, 4.3673, 5.898, 5.898, 5.898, 1.5102, 1.5102, 1.5102, 2.5306, 2.5306, 2.5306, 4.1633, 4.1633, 4.1633, 1.2041, 1.2041, 1.2041, 2.6327, 2.6327, 2.6327, 5.6939, 5.6939, 5.6939, 4.5714, 4.5714, 4.5714, 3.8571, 3.8571, 3.8571, 4.9796, 4.9796, 4.9796, 4.7755, 4.7755, 4.7755, 2.4286, 2.4286, 2.4286, 1, 1, 1, 4.8776, 4.8776, 4.8776, 3.1429, 3.1429, 3.1429, 5.1837, 5.1837, 5.1837, 3.0408, 3.0408, 3.0408, 4.4694, 4.4694, 4.4694, 4.6735, 4.6735, 4.6735, 1.6122, 1.6122, 1.6122, 2.2245, 2.2245, 2.2245, 5.5918, 5.5918, 5.5918, 3.449, 3.449, 3.449, 2.0204, 2.0204, 2.0204, 4.0612, 4.0612, 4.0612), SV5 = c(0.198, 0.198, 0.198, 0.2592, 0.2592, 0.2592, 0.2184, 0.2184, 0.2184, 0.1857, 0.1857, 0.1857, 0.1816, 0.1816, 0.1816, 0.1898, 0.1898, 0.1898, 0.1, 0.1, 0.1, 0.2714, 0.2714, 0.2714, 0.1327, 0.1327, 0.1327, 0.2143, 0.2143, 0.2143, 0.1612, 0.1612, 0.1612, 0.1041, 0.1041, 0.1041, 0.2347, 0.2347, 0.2347, 0.1694, 0.1694, 0.1694, 0.1245, 0.1245, 0.1245, 0.1408, 0.1408, 0.1408, 0.2224, 0.2224, 0.2224, 0.3, 0.3, 0.3, 0.2918, 0.2918, 0.2918, 0.2878, 0.2878, 0.2878, 0.1082, 0.1082, 0.1082, 0.2755, 0.2755, 0.2755, 0.2388, 0.2388, 0.2388, 0.1776, 0.1776, 0.1776, 0.2551, 0.2551, 0.2551, 0.1653, 0.1653, 0.1653, 0.1939, 0.1939, 0.1939, 0.1367, 0.1367, 0.1367, 0.2796, 0.2796, 0.2796, 0.2306, 0.2306, 0.2306, 0.1735, 0.1735, 0.1735, 0.2265, 0.2265, 0.2265, 0.2061, 0.2061, 0.2061, 0.2429, 0.2429, 0.2429, 0.1204, 0.1204, 0.1204, 0.251, 0.251, 0.251, 0.1449, 0.1449, 0.1449, 0.202, 0.202, 0.202, 0.2959, 0.2959, 0.2959, 0.1163, 0.1163, 0.1163, 0.1286, 0.1286, 0.1286, 0.1122, 0.1122, 0.1122, 0.2633, 0.2633, 0.2633, 0.149, 0.149, 0.149, 0.2837, 0.2837, 0.2837, 0.2673, 0.2673, 0.2673, 0.2469, 0.2469, 0.2469, 0.2102, 0.2102, 0.2102, 0.1531, 0.1531, 0.1531, 0.1571, 0.1571, 0.1571), SV6 = c(90.2041, 90.2041, 90.2041, 69.7959, 69.7959, 69.7959, 83.6735, 83.6735, 83.6735, 82.0408, 82.0408, 82.0408, 88.5714, 88.5714, 88.5714, 68.9796, 68.9796, 68.9796, 80.4082, 80.4082, 80.4082, 62.449, 62.449, 62.449, 96.7347, 96.7347, 96.7347, 75.5102, 75.5102, 75.5102, 97.551, 97.551, 97.551, 73.8776, 73.8776, 73.8776, 77.1429, 77.1429, 77.1429, 98.3673, 98.3673, 98.3673, 76.3265, 76.3265, 76.3265, 74.6939, 74.6939, 74.6939, 61.6327, 61.6327, 61.6327, 91.8367, 91.8367, 91.8367, 100, 100, 100, 68.1633, 68.1633, 68.1633, 73.0612, 73.0612, 73.0612, 82.8571, 82.8571, 82.8571, 63.2653, 63.2653, 63.2653, 81.2245, 81.2245, 81.2245, 95.9184, 95.9184, 95.9184, 86.9388, 86.9388, 86.9388, 94.2857, 94.2857, 94.2857, 71.4286, 71.4286, 71.4286, 60, 60, 60, 89.3878, 89.3878, 89.3878, 86.1224, 86.1224, 86.1224, 92.6531, 92.6531, 92.6531, 65.7143, 65.7143, 65.7143, 87.7551, 87.7551, 87.7551, 84.4898, 84.4898, 84.4898, 60.8163, 60.8163, 60.8163, 79.5918, 79.5918, 79.5918, 64.0816, 64.0816, 64.0816, 99.1837, 99.1837, 99.1837, 85.3061, 85.3061, 85.3061, 66.5306, 66.5306, 66.5306, 64.898, 64.898, 64.898, 95.102, 95.102, 95.102, 91.0204, 91.0204, 91.0204, 67.3469, 67.3469, 67.3469, 77.9592, 77.9592, 77.9592, 72.2449, 72.2449, 72.2449, 70.6122, 70.6122, 70.6122, 93.4694, 93.4694, 93.4694, 78.7755, 78.7755, 78.7755), SV7 = c(108.1633, 108.1633, 108.1633, 100, 100, 100, 197.9592, 197.9592, 197.9592, 136.7347, 136.7347, 136.7347, 230.6122, 230.6122, 230.6122, 218.3673, 218.3673, 218.3673, 263.2653, 263.2653, 263.2653, 144.898, 144.898, 144.898, 234.6939, 234.6939, 234.6939, 173.4694, 173.4694, 173.4694, 267.3469, 267.3469, 267.3469, 214.2857, 214.2857, 214.2857, 222.449, 222.449, 222.449, 271.4286, 271.4286, 271.4286, 157.1429, 157.1429, 157.1429, 140.8163, 140.8163, 140.8163, 153.0612, 153.0612, 153.0612, 148.9796, 148.9796, 148.9796, 255.102, 255.102, 255.102, 169.3878, 169.3878, 169.3878, 226.5306, 226.5306, 226.5306, 279.5918, 279.5918, 279.5918, 295.9184, 295.9184, 295.9184, 202.0408, 202.0408, 202.0408, 116.3265, 116.3265, 116.3265, 165.3061, 165.3061, 165.3061, 259.1837, 259.1837, 259.1837, 291.8367, 291.8367, 291.8367, 206.1224, 206.1224, 206.1224, 120.4082, 120.4082, 120.4082, 283.6735, 283.6735, 283.6735, 300, 300, 300, 112.2449, 112.2449, 112.2449, 287.7551, 287.7551, 287.7551, 161.2245, 161.2245, 161.2245, 251.0204, 251.0204, 251.0204, 246.9388, 246.9388, 246.9388, 177.551, 177.551, 177.551, 124.4898, 124.4898, 124.4898, 242.8571, 242.8571, 242.8571, 210.2041, 210.2041, 210.2041, 189.7959, 189.7959, 189.7959, 185.7143, 185.7143, 185.7143, 238.7755, 238.7755, 238.7755, 128.5714, 128.5714, 128.5714, 193.8776, 193.8776, 193.8776, 181.6327, 181.6327, 181.6327, 104.0816, 104.0816, 104.0816, 132.6531, 132.6531, 132.6531, 275.5102, 275.5102, 275.5102 )), crit = "aic", method = "g", confsetsize = 30, plotty = FALSE, report = FALSE, level = 2, name = "Pacioni_et_al_ST_LHS_GeneDiv", fitfunc = function (formula, data, subset, na.action, weights, offset, link = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"), link.phi = NULL, type = c("ML", "BC", "BR"), control = betareg.control(...), model = TRUE, y = TRUE, x = FALSE, ...) { cl <- match.call() if (missing(data)) data <- environment(formula) mf <- match.call(expand.dots = FALSE) m <- match(c("formula", "data", "subset", "na.action", "weights", "offset"), names(mf), 0L) mf <- mf[c(1L, m)] mf$drop.unused.levels <- TRUE oformula <- as.formula(formula) formula <- as.Formula(formula) if (length(formula)[2L] < 2L) { formula <- as.Formula(formula(formula), ~1) simple_formula <- TRUE } else { if (length(formula)[2L] > 2L) { formula <- Formula(formula(formula, rhs = 1:2)) warning("formula must not have more than two RHS parts") } simple_formula <- FALSE } mf$formula <- formula mf[[1L]] <- as.name("model.frame") mf <- eval(mf, parent.frame()) mt <- terms(formula, data = data) mtX <- terms(formula, data = data, rhs = 1L) mtZ <- delete.response(terms(formula, data = data, rhs = 2L)) Y <- model.response(mf, "numeric") X <- model.matrix(mtX, mf) Z <- model.matrix(mtZ, mf) if (length(Y) < 1) stop("empty model") if (!(min(Y) > 0 & max(Y) < 1)) stop("invalid dependent variable, all observations must be in (0, 1)") n <- length(Y) type <- match.arg(type) if (is.character(link)) link <- match.arg(link) if (is.null(link.phi)) link.phi <- if (simple_formula) "identity" else "log" if (is.character(link.phi)) link.phi <- match.arg(link.phi, c("identity", "log", "sqrt")) weights <- model.weights(mf) if (is.null(weights)) weights <- 1 if (length(weights) == 1) weights <- rep.int(weights, n) weights <- as.vector(weights) names(weights) <- rownames(mf) expand_offset <- function(offset) { if (is.null(offset)) offset <- 0 if (length(offset) == 1) offset <- rep.int(offset, n) as.vector(offset) } offsetX <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 1L, terms = TRUE))) offsetZ <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 2L, terms = TRUE))) if (!is.null(cl$offset)) offsetX <- offsetX + expand_offset(mf[, "(offset)"]) offset <- list(mean = offsetX, precision = offsetZ) rval <- betareg.fit(X, Y, Z, weights, offset, link, link.phi, type, control) rval$call <- cl rval$formula <- oformula rval$terms <- list(mean = mtX, precision = mtZ, full = mt) rval$levels <- list(mean = .getXlevels(mtX, mf), precision = .getXlevels(mtZ, mf), full = .getXlevels(mt, mf)) rval$contrasts <- list(mean = attr(X, "contrasts"), precision = attr(Z, "contrasts")) if (model) rval$model <- mf if (y) rval$y <- Y if (x) rval$x <- list(mean = X, precision = Z) class(rval) <- "betareg" return(rval) }, link = "cloglog", na.action = function (object, ...) UseMethod("na.omit")) where 6: glmulti(GeneDiv ~ SV1 * SV2 * SV3, data = list(Population = c("Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1", "Population1"), Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L, 13L, 13L, 13L, 14L, 14L, 14L, 15L, 15L, 15L, 16L, 16L, 16L, 17L, 17L, 17L, 18L, 18L, 18L, 19L, 19L, 19L, 20L, 20L, 20L, 21L, 21L, 21L, 22L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 24L, 25L, 25L, 25L, 26L, 26L, 26L, 27L, 27L, 27L, 28L, 28L, 28L, 29L, 29L, 29L, 30L, 30L, 30L, 31L, 31L, 31L, 32L, 32L, 32L, 33L, 33L, 33L, 34L, 34L, 34L, 35L, 35L, 35L, 36L, 36L, 36L, 37L, 37L, 37L, 38L, 38L, 38L, 39L, 39L, 39L, 40L, 40L, 40L, 41L, 41L, 41L, 42L, 42L, 42L, 43L, 43L, 43L, 44L, 44L, 44L, 45L, 45L, 45L, 46L, 46L, 46L, 47L, 47L, 47L, 48L, 48L, 48L, 49L, 49L, 49L, 50L, 50L, 50L), Iteration = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3), YrExt = c(8, 12, 13, NA, NA, NA, NA, NA, NA, 7, 5, 4, 19, 19, 32, 11, 13, 15, 79, 54, 83, 70, 24, 23, NA, NA, NA, 32, 34, 99, NA, NA, NA, NA, NA, NA, 33, 36, 24, NA, NA, NA, NA, NA, NA, 11, 8, 11, NA, NA, NA, 12, 4, 6, 9, 9, 10, 9, 9, 12, NA, NA, NA, NA, NA, NA, 36, 19, 30, NA, 101, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, 18, 13, NA, NA, NA, 15, 24, 21, 7, 10, 10, NA, NA, NA, 29, 24, 22, NA, NA, NA, 31, 55, 20, 33, 39, 35, 48, 50, 30, NA, NA, NA, 109, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), N = c(0, 0, 0, 1384, 1514, 605, 1364, 1366, 1108, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 13, 3, 18, 0, 0, 382, 722, 386, 0, 0, 15, 785, 814, 809, 1253, 1330, 1290, 0, 0, 0, 557, 588, 527, 385, 552, 580, 0, 0, 0, 1166, 1057, 1098, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1106, 1271, 1544, 538, 587, 541, 0, 0, 0, 88, 12, 232, 1087, 1126, 1218, 438, 390, 418, 465, 465, 437, 464, 244, 353, 408, 468, 419, 461, 291, 79, 930, 1010, 764, 663, 580, 678, 781, 796, 847, 476, 577, 603, 355, 187, 879, 0, 0, 0, 982, 996, 884, 0, 0, 0, 0, 0, 0, 1466, 1429, 1464, 0, 0, 0, 755, 731, 776, 0, 0, 0, 0, 0, 10, 0, 0, 0, 1243, 1136, 1216, 23, 52, 379, 213, 183, 81, 682, 681, 690, 1197, 1036, 993), GeneDiv = c(NA, NA, NA, 0.9605, 0.9372, 0.8284, 0.9883, 0.9839, 0.9823, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.9339, 0.9538, 0.9679, NA, NA, NA, 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108.1633, 100, 100, 100, 197.9592, 197.9592, 197.9592, 136.7347, 136.7347, 136.7347, 230.6122, 230.6122, 230.6122, 218.3673, 218.3673, 218.3673, 263.2653, 263.2653, 263.2653, 144.898, 144.898, 144.898, 234.6939, 234.6939, 234.6939, 173.4694, 173.4694, 173.4694, 267.3469, 267.3469, 267.3469, 214.2857, 214.2857, 214.2857, 222.449, 222.449, 222.449, 271.4286, 271.4286, 271.4286, 157.1429, 157.1429, 157.1429, 140.8163, 140.8163, 140.8163, 153.0612, 153.0612, 153.0612, 148.9796, 148.9796, 148.9796, 255.102, 255.102, 255.102, 169.3878, 169.3878, 169.3878, 226.5306, 226.5306, 226.5306, 279.5918, 279.5918, 279.5918, 295.9184, 295.9184, 295.9184, 202.0408, 202.0408, 202.0408, 116.3265, 116.3265, 116.3265, 165.3061, 165.3061, 165.3061, 259.1837, 259.1837, 259.1837, 291.8367, 291.8367, 291.8367, 206.1224, 206.1224, 206.1224, 120.4082, 120.4082, 120.4082, 283.6735, 283.6735, 283.6735, 300, 300, 300, 112.2449, 112.2449, 112.2449, 287.7551, 287.7551, 287.7551, 161.2245, 161.2245, 161.2245, 251.0204, 251.0204, 251.0204, 246.9388, 246.9388, 246.9388, 177.551, 177.551, 177.551, 124.4898, 124.4898, 124.4898, 242.8571, 242.8571, 242.8571, 210.2041, 210.2041, 210.2041, 189.7959, 189.7959, 189.7959, 185.7143, 185.7143, 185.7143, 238.7755, 238.7755, 238.7755, 128.5714, 128.5714, 128.5714, 193.8776, 193.8776, 193.8776, 181.6327, 181.6327, 181.6327, 104.0816, 104.0816, 104.0816, 132.6531, 132.6531, 132.6531, 275.5102, 275.5102, 275.5102 )), crit = "aic", method = "g", confsetsize = 30, plotty = FALSE, report = FALSE, level = 2, name = "Pacioni_et_al_ST_LHS_GeneDiv", fitfunc = function (formula, data, subset, na.action, weights, offset, link = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"), link.phi = NULL, type = c("ML", "BC", "BR"), control = betareg.control(...), model = TRUE, y = TRUE, x = FALSE, ...) { cl <- match.call() if (missing(data)) data <- environment(formula) mf <- match.call(expand.dots = FALSE) m <- match(c("formula", "data", "subset", "na.action", "weights", "offset"), names(mf), 0L) mf <- mf[c(1L, m)] mf$drop.unused.levels <- TRUE oformula <- as.formula(formula) formula <- as.Formula(formula) if (length(formula)[2L] < 2L) { formula <- as.Formula(formula(formula), ~1) simple_formula <- TRUE } else { if (length(formula)[2L] > 2L) { formula <- Formula(formula(formula, rhs = 1:2)) warning("formula must not have more than two RHS parts") } simple_formula <- FALSE } mf$formula <- formula mf[[1L]] <- as.name("model.frame") mf <- eval(mf, parent.frame()) mt <- terms(formula, data = data) mtX <- terms(formula, data = data, rhs = 1L) mtZ <- delete.response(terms(formula, data = data, rhs = 2L)) Y <- model.response(mf, "numeric") X <- model.matrix(mtX, mf) Z <- model.matrix(mtZ, mf) if (length(Y) < 1) stop("empty model") if (!(min(Y) > 0 & max(Y) < 1)) stop("invalid dependent variable, all observations must be in (0, 1)") n <- length(Y) type <- match.arg(type) if (is.character(link)) link <- match.arg(link) if (is.null(link.phi)) link.phi <- if (simple_formula) "identity" else "log" if (is.character(link.phi)) link.phi <- match.arg(link.phi, c("identity", "log", "sqrt")) weights <- model.weights(mf) if (is.null(weights)) weights <- 1 if (length(weights) == 1) weights <- rep.int(weights, n) weights <- as.vector(weights) names(weights) <- rownames(mf) expand_offset <- function(offset) { if (is.null(offset)) offset <- 0 if (length(offset) == 1) offset <- rep.int(offset, n) as.vector(offset) } offsetX <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 1L, terms = TRUE))) offsetZ <- expand_offset(model.offset(model.part(formula, data = mf, rhs = 2L, terms = TRUE))) if (!is.null(cl$offset)) offsetX <- offsetX + expand_offset(mf[, "(offset)"]) offset <- list(mean = offsetX, precision = offsetZ) rval <- betareg.fit(X, Y, Z, weights, offset, link, link.phi, type, control) rval$call <- cl rval$formula <- oformula rval$terms <- list(mean = mtX, precision = mtZ, full = mt) rval$levels <- list(mean = .getXlevels(mtX, mf), precision = .getXlevels(mtZ, mf), full = .getXlevels(mt, mf)) rval$contrasts <- list(mean = attr(X, "contrasts"), precision = attr(Z, "contrasts")) if (model) rval$model <- mf if (y) rval$y <- Y if (x) rval$x <- list(mean = X, precision = Z) class(rval) <- "betareg" return(rval) }, link = "cloglog", na.action = function (object, ...) UseMethod("na.omit")) where 7: do.call("glmulti", list(formula, data = data, crit = ic, method = m, confsetsize = set_size, plotty = FALSE, report = FALSE, level = l, name = name, fitfunc = betareg::betareg, link = links[linkpos], na.action = na.omit)) where 8: system.time(best.mod <- do.call("glmulti", list(formula, data = data, crit = ic, method = m, confsetsize = set_size, plotty = FALSE, report = FALSE, level = l, name = name, fitfunc = betareg::betareg, link = links[linkpos], na.action = na.omit))) where 9 at test-fit_regression.R#38: fit_regression(data = lrun.ST_LHS.no.base, lookup = lkup.ST_LHS, census = FALSE, project = "Pacioni_et_al", scenario = "ST_LHS", popn = 1, param = "GeneDiv", vs = c("SV1", "SV2", "SV3"), l = 2, ncand = 30, save2disk = FALSE) where 10: eval(code, test_env) where 11: eval(code, test_env) where 12: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() } }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error) where 13: doTryCatch(return(expr), name, parentenv, handler) where 14: tryCatchOne(expr, names, parentenv, handlers[[1L]]) where 15: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) where 16: doTryCatch(return(expr), name, parentenv, handler) where 17: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) where 18: tryCatchList(expr, classes, parentenv, handlers) where 19: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() } }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { }) where 20: test_code(desc, code, env = parent.frame(), reporter = reporter) where 21 at test-fit_regression.R#6: test_that("fit-regressin", { data(pac.run.lhs, pac.lhs) pac.lhs.no.base <- pac.lhs[!pac.lhs$scen.name == "ST_LHS(Base)", ] lkup.ST_LHS <- lookup_table(data = pac.lhs.no.base, project = "Pacioni_et_al", scenario = "ST_LHS", pop = "Population 1", SVs = c("SV1", "SV2", "SV3", "SV4", "SV5", "SV6", "SV7"), save2disk = FALSE) lrun.ST_LHS.no.base <- pac.run.lhs[[2]][!pac.run.lhs[[2]]$Scenario == "ST_LHS(Base)", ] reg <- fit_regression(data = lrun.ST_LHS.no.base, lookup = lkup.ST_LHS, census = FALSE, project = "Pacioni_et_al", scenario = "ST_LHS", popn = 1, param = "N", vs = c("SV1", "SV2", "SV3"), l = 2, ncand = 30, save2disk = FALSE) expect_is(reg, "glmulti") coefs <- coef(reg@objects[[1]]) expect_true(round(0.0038677, 6) == round(coefs["SV1"], 6)) reg.prop <- fit_regression(data = lrun.ST_LHS.no.base, lookup = lkup.ST_LHS, census = FALSE, project = "Pacioni_et_al", scenario = "ST_LHS", popn = 1, param = "GeneDiv", vs = c("SV1", "SV2", "SV3"), l = 2, ncand = 30, save2disk = FALSE) expect_is(reg.prop, "glmulti") coefs <- coef(reg.prop@objects[[1]]) expect_true(round(0.0001663474, 6) == round(coefs["SV1"], 6)) reg.prop2 <- fit_regression(data = lrun.ST_LHS.no.base, lookup = lkup.ST_LHS, census = FALSE, links = c("logit", "probit", "cauchit", "loglog"), project = "Pacioni_et_al", scenario = "ST_LHS", popn = 1, param = "GeneDiv", vs = c("SV1", "SV2", "SV3"), l = 2, ncand = 30, save2disk = FALSE) coefs <- coef(reg.prop2@objects[[1]]) expect_true(round(0.0002583495, 6) == round(coefs["SV1"], 6)) }) where 22: eval(code, test_env) where 23: eval(code, test_env) where 24: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() } }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error) where 25: doTryCatch(return(expr), name, parentenv, handler) where 26: tryCatchOne(expr, names, parentenv, handlers[[1L]]) where 27: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) where 28: doTryCatch(return(expr), name, parentenv, handler) where 29: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) where 30: tryCatchList(expr, classes, parentenv, handlers) where 31: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() } }, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { }) where 32: test_code(NULL, exprs, env) where 33: source_file(path, child_env(env), wrap = wrap) where 34: FUN(X[[i]], ...) where 35: lapply(test_paths, test_one_file, env = env, wrap = wrap) where 36: doTryCatch(return(expr), name, parentenv, handler) where 37: tryCatchOne(expr, names, parentenv, handlers[[1L]]) where 38: tryCatchList(expr, classes, parentenv, handlers) where 39: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL }) where 40: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, wrap = wrap)) where 41: test_files(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, wrap = wrap, load_package = load_package) where 42: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, wrap = wrap, load_package = load_package, parallel = parallel) where 43: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed") where 44: test_check("vortexR") --- value of length: 90 type: logical --- [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [85] FALSE FALSE FALSE FALSE FALSE FALSE --- function from context --- Method Definition: function (y, xr, data, exclude = c(), name = "glmulti.analysis", intercept = TRUE, marginality = FALSE, bunch = 30, chunk = 1, chunks = 1, level = 2, minsize = 0, maxsize = -1, minK = 0, maxK = -1, method = "h", crit = "aic", confsetsize = 100, popsize = 100, mutrate = 10^-3, sexrate = 0.1, imm = 0.3, plotty = TRUE, report = TRUE, deltaM = 0.05, deltaB = 0.05, conseq = 5, fitfunction = "glm", resumefile = "id", includeobjects = TRUE, ...) { if (report) write("Initialization...", file = "") if (method == "h") DELTAD = 50 else DELTAD = 10 x <- unique(xr) excluzt <- unique(exclude) databis = model.frame(as.formula(paste(y, "~", paste(x, sep = "", collapse = "+"), sep = "")), data = data) ssize <- length(databis[, 1]) xc <- c("qazxcww") xq <- c("qazxcww") nc <- 0 nq <- 0 nana = names(databis) for (i in x) if (is.factor(databis[[which(nana == i)]])) { nc <- nc + 1 xc <- c(xc, i) } else { nq <- nq + 1 xq <- c(xq, i) } excluz = c("qazxcww", excluzt) support = match.fun(crit) if (is.function(crit)) crit = deparse(substitute(crit)) fitfunc = match.fun(fitfunction) if (is.function(fitfunction)) fitfunction <- deparse(substitute(fitfunction)) if (method == "r") { write("Restoring from files...", file = "") if (resumefile == "id") molly <- .jcall("glmulti/Resumator", "Lglmulti/ModelGenerator;", "resto", name) else molly <- .jcall("glmulti/Resumator", "Lglmulti/ModelGenerator;", "resto", resumefile) if (!.jfield(molly, "Z", "ok")) { warning("!Could not restore analysis from files.") return(-1) } } else { molly <- .jnew("glmulti/ModelGenerator", y, .jarray(xc), .jarray(xq), .jarray(excluz), as.integer(level), as.integer(minsize), as.integer(maxsize), as.integer(minK), as.integer(maxK), intercept, marginality) if (!.jfield(molly, "Z", "ok")) { warning("!Oversized candidate set.") return(-1) } okidok = T if (method != "l") if (level == 1) { okidok = (nc <= 32 && nq <= 32) } else { okidok = (nc < 16 && nq < 16 && nc * nq < 128) } if (!okidok) { warning("!Too many predictors.") return(-1) } if (nc > 0) { flevs = integer(nc) for (i in 1:nc) flevs[i] <- as.integer(nlevels(databis[, which(nana == xc[i + 1])])) .jcall(molly, "V", "supplyNbLev", .jarray(flevs)) } else .jcall(molly, "V", "supplyNbLev", .jarray(integer(2))) options(warn = -1) .jcall(molly, "V", "supplyErrorDF", as.integer(attr(logLik(fitfunc(as.formula(paste(y, "~1")), data = data, ...)), "df") - 1)) options(warn = 0) } if (method == "d") { write("TASK: Diagnostic of candidate set.", file = "") write(paste("Sample size:", ssize), file = "") write(paste(nc, "factor(s)."), file = "") write(paste(nq, "covariate(s)."), file = "") write(paste(.jfield(molly, "I", "nbforbxc"), "f exclusion(s)."), file = "") write(paste(.jfield(molly, "I", "nbforbxq"), "c exclusion(s)."), file = "") write(paste(.jfield(molly, "I", "nbforbxcxc"), "f:f exclusion(s)."), file = "") write(paste(.jfield(molly, "I", "nbforbxqxq"), "c:c exclusion(s)."), file = "") write(paste(.jfield(molly, "I", "nbforbxcxq"), "f:c exclusion(s)."), file = "") write(paste("Size constraints: min = ", minsize, "max =", maxsize), file = "") write(paste("Complexity constraints: min = ", minK, "max =", maxK), file = "") if (marginality) write("Marginality rule.", file = "") nbcand = .jcall(molly, "I", "diagnose") if (nbcand == -1) write("Your candidate set contains more than 1 billion (1e9) models.", file = "") else write(paste("Your candidate set contains", nbcand, "models."), file = "") return(nbcand) } if (method == "h") { if (report) write("TASK: Exhaustive screening of candidate set.", file = "") resulto <- new("glmulti") if (chunks > 1) { resulto@name = paste(name, "_", chunk, ".", chunks, sep = "") } else resulto@name = name resulto@params = list(name = name, intercept = intercept, marginality = marginality, bunch = bunch, chunk = chunk, chunks = chunks, level = level, minsize = minsize, maxsize = maxsize, minK = minK, maxK = maxK, method = method, crit = crit, confsetsize = confsetsize, fitfunction = fitfunction) resulto@call = match.call() resulto@adi = list(...) if (report) write("Fitting...", file = "") flush.console() if (!.jcall(molly, "Z", "produceModels", as.integer(chunk), as.integer(chunks), as.integer(bunch))) { warning("!Failed to start Java thread.") return(-1) } lesCrit <- numeric(confsetsize) lesK <- vector("integer", confsetsize) lesForms <- vector("character", confsetsize) lesObjects = list() curr <- 0 sel <- 0 while (.jcall(molly, "Z", "nextModel")) { formula <- .jcall(molly, "[S", "getCurrModel") beber <- lapply(formula, function(x) if (!is.na(x)) fitfunc(as.formula(x), data = data, ...) else NA) for (momo in 1:bunch) { curr = curr + 1 proceed = !is.na(formula[momo]) if (proceed && fitfunction == "glm" && !beber[[momo]]$converged) { proceed <- FALSE warning(paste("!fitting function failed to converge. Model skipped: ", formula, sep = "")) } if (proceed) { cricri <- support(beber[[momo]]) if (sel < confsetsize) { sel = sel + 1 lesForms[sel] = formula[momo] lesCrit[sel] = cricri lesK[sel] = attr(logLik(beber[[momo]]), "df") lesObjects = c(lesObjects, list(beber[[momo]])) } else { mini = max(lesCrit) if (cricri < mini) { ou = which(lesCrit == mini)[1] lesForms[ou] = formula[momo] lesCrit[ou] = cricri lesK[ou] = attr(logLik(beber[[momo]]), "df") lesObjects[[ou]] = beber[[momo]] } } } if (curr%%(DELTAD) == 0) { if (report) { write(paste("\nAfter ", curr, " models:", sep = ""), file = "") bestofsex = min(lesCrit[1:sel]) write(paste("Best model: ", gsub(" ", "", lesForms[which(lesCrit == bestofsex)]), sep = ""), file = "") write(paste("Crit= ", bestofsex, sep = ""), file = "") write(paste("Mean crit= ", mean(lesCrit[1:sel]), sep = ""), file = "") flush.console() } if (plotty) { plot(sort(lesCrit[1:sel]), xlab = "Best models", ylab = paste("Support (", crit, ")"), pch = 19, main = "IC profile") abline(h = bestofsex + 2, col = "red") } } } } if (report) write("Completed.", file = "") reglo <- order(lesCrit[1:sel]) resulto@crits = lesCrit[1:sel][reglo] resulto@formulas = lapply(lesForms[1:sel][reglo], as.formula) resulto@K = as.integer(lesK[1:sel][reglo]) resulto@nbmods = as.integer(sel) if (includeobjects) resulto@objects = lesObjects[reglo] else resulto@objects = list() return(resulto) } else if (method == "l") { if (report) write("TASK: Exhaustive screening of candidate set, branch-and-bound algorithm.", file = "") write("[ Be sure to have package leaps installed ]", file = "") if (level == 2 || nc > 0) stop("Method l cannot be used with factors or interactions") fitfunction = "lm" resulto <- new("glmulti") resulto@name = name resulto@params = list(name = name, intercept = intercept, marginality = marginality, chunk = chunk, chunks = chunks, level = level, minsize = minsize, maxsize = maxsize, minK = minK, maxK = maxK, method = method, crit = crit, confsetsize = confsetsize, fitfunction = fitfunction) resulto@call = match.call() resulto@adi = list(...) if (report) write("Fitting...", file = "") flush.console() f <- as.formula(paste(y, paste(xq[-1], collapse = "+"), sep = "~")) lilo <- try(regsubsets(f, data = databis, nbest = confsetsize, really.big = T, intercept = intercept), silent = F) if (class(lilo) == "try-error") stop("!call to regsubsets failed.") mama <- summary(lilo, matrix = T, matrix.logical = T) coda <- mama[[7]] lesrss <- mama[[3]] nbmods = length(coda[, 1]) KK <- as.numeric(sapply(dimnames(coda)[[1]], function(x) strsplit(x, split = " ")[[1]][1])) pena = 0 if (intercept) pena = 1 sssize <- length(resid(lm(as.formula(paste(y, "1", sep = "~")), data = databis))) if (crit == "aicc") lesic <- as.numeric(lapply(1:nbmods, function(x) sssize * log(lesrss[x]/sssize) + 2 * (KK[x] + 1 + pena) * sssize/max(0, sssize - KK[x] - 2 - pena))) else if (crit == "aic") lesic <- as.numeric(lapply(1:nbmods, function(x) sssize * log(lesrss[x]/sssize) + 2 * (KK[x] + 1 + pena))) else lesic <- as.numeric(lapply(1:nbmods, function(x) sssize * log(lesrss[x]/sssize) + log(sssize) * (KK[x] + 1 + pena))) if (intercept) { nullos <- sum(lm(as.formula(paste(y, "1", sep = "~")), data = databis)$residuals^2) if (crit == "aicc") icnull <- sssize * log(nullos/sssize) + 2 * (1 + pena) * sssize/max(0, sssize - 2 - pena) else if (crit == "aic") icnull <- sssize * log(nullos/sssize) + 2 * (1 + pena) else icnull <- sssize * log(nullos/sssize) + log(sssize) * (1 + pena) KK = c(KK, 0) lesic = c(lesic, icnull) coda = rbind(coda, rep(F, length(coda[1, ]))) nbmods = nbmods + 1 } if (report) write("Completed.", file = "") oo <- order(lesic) lesic <- lesic[oo] KK <- KK[oo] coda <- coda[oo, ] nbbyk = tapply(KK, KK, length) worro = tapply(lesic, KK, max) if (max(nbbyk) == confsetsize) thresh = min(worro[nbbyk == confsetsize]) else thresh = max(worro) KK <- KK[lesic <= thresh] coda <- coda[lesic <= thresh, ] lesic = lesic[lesic <= thresh] nbmodels = length(KK) if (report) write(paste(nbmodels, "first best models identified."), file = "") resulto@crits = lesic resulto@K = as.integer(KK + 1 + pena) formo <- apply(coda, 1, function(x) { if (intercept) as.formula(paste(y, paste(c("1", xq[-1][x]), collapse = "+"), sep = "~")) else as.formula(paste(y, paste(c("-1", xq[-1][x]), collapse = "+"), sep = "~")) }) resulto@formulas = formo resulto@nbmods = as.integer(nbmodels) if (includeobjects) { fitfunc = match.fun(fitfunction) lesObjects = lapply(formo, function(x) fitfunc(x, data = data, ...)) resulto@objects = lesObjects } return(resulto) } else { write("TASK: Genetic algorithm in the candidate set.", file = "") resulto <- new("glmulti") resulto@name = name resulto@params = list(name = name, intercept = intercept, marginality = marginality, bnch = bunch, chunk = chunk, chunks = chunks, level = level, minsize = minsize, maxsize = maxsize, minK = minK, maxK = maxK, method = method, crit = crit, confsetsize = confsetsize, fitfunction = fitfunction, popsize = popsize, mutrate = mutrate, sexrate = sexrate, imm = imm, plotty = plotty, deltaM = deltaM, deltaB = deltaB, conseq = conseq, resumefile = resumefile) resulto@call = match.call() resulto@adi = list(...) lesObjects = list() write("Initialization...", file = "") currgen = 0 consoude = 0 gogo = TRUE bestofsex = 10000 minou = 10000 bestofsexN = 1000 minouN = 1000 if (method == "r") popul = .jcall(molly, "[S", "initPopAgain", mutrate, imm, sexrate, name) else popul = .jcall(molly, "[S", "initPop", as.integer(popsize), mutrate, imm, sexrate, as.integer(confsetsize), name) tini = Sys.time() dyniT = numeric(0) dyniB = numeric(0) dyniM = numeric(0) write("Algorithm started...", file = "") while (gogo) { for (i in 1:DELTAD) { nbtofit = length(popul) lesic = numeric(nbtofit) if (nbtofit > 0) for (m in 1:nbtofit) { formula = popul[m] beber <- fitfunc(as.formula(formula), data = data, ...) liliac <- logLik(beber) K <- attr(liliac, "df") if (fitfunction == "glm" && !beber$converged) lesic[m] = 10000 else lesic[m] = support(beber) } currgen = currgen + 1 popul = .jcall(molly, "[S", "nextGeneration", .jarray(lesic)) } lesCrit = .jcall(molly, "[D", "reportConfIC") bestofsexN = .jcall(molly, "D", "reportBestIC") minouN = .jcall(molly, "D", "reportMeanIC") bestform = .jcall(molly, "S", "reportbestModel") dyniT = c(dyniT, as.numeric(Sys.time() - tini)) dyniB = c(dyniB, bestofsexN) dyniM = c(dyniM, minouN) if (report) { write(paste("\nAfter ", currgen, " generations:", sep = ""), file = "") write(paste("Best model: ", gsub(" ", "", bestform), sep = ""), file = "") write(paste("Crit= ", bestofsexN, sep = ""), file = "") write(paste("Mean crit= ", minouN, sep = ""), file = "") flush.console() } .jcall(molly, "V", "printImage") if (plotty) { plot(sort(lesCrit), xlab = "Best models", ylab = paste("Support (", crit, ")"), pch = 19, main = "IC profile") abline(h = bestofsexN + 2, col = "red") } if (length(lesCrit) == confsetsize && minouN - minou >= -deltaM && bestofsexN - bestofsex >= -deltaB) consoude = consoude + 1 else consoude = 0 if (consoude == conseq) { write("Improvements in best and average IC have bebingo en below the specified goals.", file = "") write("Algorithm is declared to have converged.", file = "") gogo = FALSE } else { if (report) write(paste("Change in best IC:", bestofsexN - bestofsex, "/ Change in mean IC:", minouN - minou), file = "") minou = minouN bestofsex = bestofsexN } } write("Completed.", file = "") lesForms = .jcall(molly, "[S", "reportConfMods") lesKK = .jcall(molly, "[I", "reportConfKs") sel = length(lesCrit) reglo <- order(lesCrit) resulto@crits = lesCrit[reglo] resulto@formulas = lapply(lesForms[reglo], as.formula) resulto@K = as.integer(lesKK)[reglo] resulto@nbmods = as.integer(sel) if (includeobjects) { lesObjects = lapply(lesForms[reglo], function(x) if (!is.na(x)) fitfunc(as.formula(x), data = data, ...) else NA) resulto@objects = lesObjects } resulto@params = c(resulto@params, list(generations = currgen, elapsed = as.numeric(Sys.time() - tini), dynat = dyniT, dynab = dyniB, dynam = dyniM)) return(resulto) } } Signatures: y xr data exclude target "character" "character" "data.table" "character" defined "character" "character" "ANY" "ANY" --- function search by body --- S4 Method glmulti:glmulti defined in namespace glmulti with signature character#character#ANY#ANY has this body. ----------- END OF FAILURE REPORT -------------- Fatal error: length > 1 in coercion to logical * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking re-building of vignette outputs ... [15s/15s] OK * checking PDF version of manual ... OK * checking for non-standard things in the check directory ... OK * checking for detritus in the temp directory ... OK * DONE Status: 1 ERROR See ‘/data/gannet/ripley/R/packages/tests-LENGTH1/vortexR.Rcheck/00check.log’ for details. Command exited with non-zero status 1 Time 3:41.34, 146.09 + 14.16