Я пытаюсь проверить соответствие модели glmm с обратным гауссовым распределением, используя пакет DHARMa.
library(lme4)
library(DHARMa)
glmm2<-glmer(time ~ noise + md+ (1|id),
data=data,
family=inverse.gaussian(link="identity"))
sim<-simulateResiduals(glmm2)
Тем не менее, я получаю это сообщение об ошибке:
Error in sfun(object, nsim = 1, ftd = rep_len(musim, n * nsim), wts = weights) :
could not find function "sfun"
Однако код работает нормально с другими дистрибутивами.
Это может быть та же проблема, что иразмещено здесь: https://github.com/lme4/lme4/issues/284 После прочтения этой темы Бен Болкер недавно исправил проблему lme4 с дистрибутивом inverse.gaussian, однако обновление пакета "lme4" с помощью install.packages() не решило проблему. Может ли это быть из-за того, что исправленное исправление еще не в CRAN (только GitHub), или это отдельная проблема?
Вот некоторые данные, которые можно сделать воспроизводимым примером (хотя я не думаю, что этопроблема с этими конкретными данными):
data<-structure(list(time = c(41.13741586, 9.782034165, 28.43048335,
3.207626451, 3.28737433, 12.17147616, 6.846317411, 7.060553219,
9.551505159, 1.946177066, 7.792069828, 3.391127888, 5.691814361,
6.093369116, 8.293302802, 7.56783162, 3.780120891, 9.783027043,
4.24972651, 2.876613826, 3.601603686, 29.13667211, 3.424758707,
3.675592368, 13.0437798, 7.547469641, 8.842781853, 8.300757096,
2.979181386, 3.419450337, 16.45199251, 3.127217308, 8.747828301,
3.428571841, 3.70943289, 11.04721516, 2.903853931, 3.440767391,
2.785837122, 3.269951103, 2.410238878, 3.89081111, 4.619280336,
2.992322509, 5.783528547, 34.00289472, 24.44992761, 23.23027649,
9.014569882, 5.894704299, 3.055185939, 2.218424498, 6.382338632,
2.755323799, 7.076236215, 3.262103618, 3.922126491, 23.61442673,
18.48894273, 4.800960669, 2.48269627, 3.146589815, 6.439999987,
7.668507118, 6.419151537, 3.542393771, 3.043635607, 2.884369079,
2.491696809, 27.55352679, 1.897232137, 2.588586002, 4.559529659,
5.193832311, 6.66462235, 7.575937154, 4.267289699, 3.077610554,
2.539769396, 11.04715723, 3.938594629, 2.990035169, 11.62055069,
6.286390667, 3.066117908, 3.036437669, 14.09709544, 2.247126905,
3.437216412, 2.22807457, 4.380971792, 2.947254937, 8.787878448,
3.107896369, 11.28890645, 3.550776501, 7.142133246, 2.362423895,
4.305386462, 9.045445478, 3.267399008, 4.677552175, 4.718496658,
3.600337195, 10.44240212, 10.15304052, 9.183458325, 5.928181431,
25.03263407, 3.076395187, 24.38716969, 2.239600859, 2.172207797,
8.76376451, 3.183504181, 2.35993369, 8.295343346, 3.418330144,
3.620356333, 10.54711979, 14.21928106, 10.37029106, 6.031589426,
3.981959804, 5.342755734, 7.904376564, 5.718102126, 3.410403438,
9.692149582, 3.13309998, 19.3245972, 4.335996613, 4.841560445,
12.32188778, 45.52278629, 2.752979722, 12.47383626, 2.134412308,
14.44585039, 16.10740155, 5.788136583, 4.511246787, 16.7312537,
3.73230319, 4.897898902, 6.028128975, 52.0381691, 4.068210128,
6.398227764, 6.118767994, 8.548906531, 3.390646287, 2.490769614,
4.111526974, 4.832608955, 8.289365702, 50.2465904, 2.646893295,
9.719880568, 4.641543, 4.771943998, 3.706358115, 4.166786292,
4.179320836, 19.52129995, 3.174416789, 6.275250101, 3.749363137,
5.181954223, 5.163764939, 6.324603377, 6.036336947, 2.908604885,
4.982428475, 6.323173522, 3.64608021, 11.80631532, 3.387963324,
14.29897945, 3.482688516, 9.645221336, 62.40574289, 3.706740696,
20.86882567, 3.251831744, 4.462031664, 15.50260099, 6.022609352,
9.416738158, 8.162124214, 16.92103384, 4.452837389, 33.60315353,
2.323210606, 4.633791727, 10.51593419, 9.167247429, 3.827658235,
3.828607871, 3.829411261, 20.42109578, 3.272191767, 13.08373561,
9.823979107, 2.954488994, 5.89699479, 17.77766321, 14.2193287,
4.84425791, 3.046470241, 4.376652312, 4.075512895, 4.447326956,
3.828587987, 3.301959055, 3.266122424, 5.958960708, 9.809333414,
3.370849736, 3.434066392, 8.531563826, 2.380370139, 11.32306372,
30.78310772, 3.105894163, 2.326072315, 5.804816817, 45.1877515,
5.479398096, 3.452887784, 8.392957238, 3.594501224, 4.455098706,
5.13784923, 4.560898241, 17.59137752, 5.411802079, 6.662678284,
6.724703395, 3.416384684, 3.478441765, 18.28886191, 16.76116317,
16.98330296, 12.38336171, 39.52376287, 7.454258623, 4.174623206,
7.837446903, 4.988091336, 4.781385826, 3.463154542, 3.464226543,
25.43735658, 3.067537685, 4.258702803, 7.340216019, 49.14047038,
2.442459709, 9.447392998, 3.197442493, 10.22828166, 4.628425949,
9.199019126, 3.482760092, 4.764069625, 4.705087528, 8.058345229,
3.430036022, 66.06439786, 10.77330705, 3.786447776, 10.80383314,
3.757634691, 17.21945979, 9.280765277, 5.620796286, 3.512069001,
4.904388737, 6.275277039, 13.81807132, 4.628234066, 2.979297419,
3.290358325, 10.74032344, 13.65048463, 4.281098604, 8.967766237,
4.149626936, 2.59, 12.85102282, 23.00134089, 4.814198164, 4.564720885,
7.195367624, 4.696707842, 9.477280147, 6.887927244, 19.009986,
4.660588773, 13.41105483, 4.041755049, 3.173568488, 4.533755494,
21.314069, 6.814173148, 7.955226733, 3.486861445, 28.51746697,
12.26761549, 47.51824882, 7.208537936, 5.800505255, 3.860646939,
43.02148852, 18.30155857, 8.401628238, 5.581668235, 40.0252368,
41.82807892, 15.43939019, 43.93014117, 8.546396018, 18.18405266,
11.05878955, 6.290103866, 3.290309576, 11.79316794, 12.91487095,
55.84556727, 4.41720961, 7.462505685, 11.52409499, 9.08413754,
3.654474629, 3.774640913, 11.77560963, 5.246143327, 4.528003446,
3.720297554, 26.86158631, 3.121956906, 3.814112187, 3.915468981,
3.855898118, 6.066957123, 5.818204851, 15.38006946, 4.82077121,
5.601840547, 8.673335565, 94.57364072, 11.72416331, 3.857151745,
12.63774199, 3.077864042, 22.91825688, 4.779887153, 3.02290964,
65.38458973, 14.61544757, 4.589837739, 30.27093406, 8.562364255,
9.152543612, 7.5945589, 13.78637596, 20.53718869, 15.09996703,
10.51215369, 22.19312527, 4.103858301, 72.50651558, 5.917881591,
3.918046252, 25.73809912, 10.11106179, 4.611947838, 3.812338842,
66.11236733, 3.083073479, 3.923163416, 4.274799646, 5.147559259,
8.04819077, 7.429203003, 77.1197558, 4.241240055, 18.20449757,
12.15671963, 12.63195774, 73.33069624, 31.72095844, 6.66150562,
23.73213392, 4.694739577, 3.798945831, 15.67155682, 10.48168672,
5.333182065, 4.850010439, 7.652005471, 4.532210133, 4.402485395,
35.35353175, 3.903941738, 3.184677454, 18.55515345, 2.687618202,
2.818215173, 10.03921751, 18.5694306, 15.06234012, 7.16657676,
9.080463855, 22.45095501, 7.831502889, 4.232363182, 66.17311789,
7.304880603, 6.61580356, 6.178855732, 5.060957087, 8.331560974,
3.81257565, 4.744033321, 8.284062198, 4.095163125, 50.18527387,
4.467955136, 7.55798715, 93.1895922, 9.163073489, 4.843419754,
3.495555564, 21.29713932, 6.607945438, 9.949066825, 5.671821957,
4.052717444, 4.392775373, 6.805400321, 4.67567415, 3.61639655,
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88.713231, 47.87339455, 4.184470597, 5.814770604, 7.722124227,
26.91274215, 22.26364589, 10.32376603, 38.02472068, 6.755221955,
6.655862961, 12.47736033, 3.832455267, 5.794588666, 2.29488901,
4.825032889, 5.707439328, 8.237935874, 3.398480834, 5.020340238,
16.54083878, 3.872542885, 88.54425795, 5.625607924, 32.84691682,
3.567019038, 17.90767527, 4.201325706, 7.412715166, 5.096011771,
98.45740835, 35.65809944, 6.7282369, 5.479067069, 3.009588285,
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3.650345073, 6.560421815, 65.29056106, 12.65290021, 14.25446065,
2.534825382, 3.594919078, 6.195722329, 68.28617492, 21.81716823,
7.727936448, 73.08995666, 7.790689, 5.263312258, 22.09589367,
9.419771743, 9.770269026, 7.020954402, 23.4026281, 8.625718029,
18.406882, 4.657678486, 11.65835826, 10.45855645, 6.720511821,
9.492626932, 20.41736393, 5.287491136, 17.4677231, 47.21784241,
4.230403918, 6.071208513, 44.32271069, 13.41734888, 47.57801238,
8.772598635, 9.205175901, 8.55700878, 4.897450519, 4.737495931,
4.338049612, 6.215468258, 4.165600023, 5.036888453, 9.569007641,
6.071899787, 7.542304652, 4.732480187, 3.442827096, 41.35375961,
4.353765853, 3.753951093, 4.664248723, 60.85668314, 80.35729941,
12.89760767, 3.989420233, 35.96090859, 6.392164591, 4.392808509,
11.64349675, 15.16356068, 26.66641769, 10.30722888, 4.189055807,
26.46911323, 19.37062122, 2.591032044, 27.77127424, 12.09154189,
62.07235295, 5.432750085, 6.406463399, 47.77777956, 7.039493391,
4.221247722, 68.8818966, 24.38479969, 8.887155651, 12.18805931,
4.821592099, 15.80203651, 8.702592898, 59.69323291, 6.059270163,
11.45979501, 39.40068331, 3.901232778, 4.811936493, 5.465225016,
8.156093384, 3.497747496, 6.628207287, 13.90997849, 10.91123037,
7.823507377, 17.41400512, 3.335581008, 8.165933257, 8.858253615,
3.11079724, 11.54130872, 8.642978559, 9.713731749, 4.457465386,
20.51801412, 7.558962511, 19.09083352, 3.111885984, 4.773125492,
3.936568118, 5.317176674, 23.43778227, 15.63826616, 36.44002133,
13.38015732, 5.292505485, 4.783865063, 22.66444017, 20.60565127,
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3.460327443, 15.40073695, 2.682902487, 5.774015487, 67.56871224,
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62.89981678, 4.4, 31.40239036, 12.29444914, 7.385797172, 10.19820787,
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67.91582164, 4.216706087, 9.11802591, 13.41809671, 38.11920761,
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6.281168569, 7.602319351, 11.60387192, 13.1849234, 5.605190238,
5.855195352, 21.38760878, 3.88769096, 7.078750029), noise = c(2L,
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3L, 5L, 3L, 3L, 5L, 2L, 2L, 3L, 2L, 2L, 4L, 5L, 5L, 1L, 5L, 4L,
3L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 4L, 1L, 2L, 4L, 4L, 3L, 3L,
4L, 2L, 3L, 5L, 3L, 3L, 3L, 2L, 2L, 4L, 2L, 5L, 2L, 4L, 5L, 3L,
2L, 5L, 4L, 2L, 3L, 4L, 2L, 4L, 4L, 3L, 2L, 3L, 5L, 2L, 3L, 3L,
4L, 2L, 3L, 5L, 4L, 4L, 3L, 4L, 3L, 5L, 2L, 4L, 2L, 3L, 2L, 3L,
3L, 2L, 2L, 5L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 4L, 5L, 5L, 5L,
2L, 2L, 5L, 4L, 3L, 3L, 5L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 4L,
2L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 3L, 2L, 4L, 4L, 1L, 3L, 3L, 2L,
2L, 3L, 2L, 4L, 3L, 2L, 3L, 2L, 4L, 2L, 2L, 4L, 2L, 5L, 2L, 4L,
2L, 5L, 2L, 3L, 5L, 4L, 1L, 2L, 4L, 2L, 2L, 4L, 4L, 5L, 5L, 2L,
2L, 5L, 4L, 2L, 3L, 4L, 2L, 4L, 4L, 2L, 2L, 5L, 4L, 2L, 2L, 4L,
4L, 2L, 2L, 3L, 2L, 2L, 5L, 4L, 4L, 4L, 2L, 3L, 4L, 5L, 1L, 2L,
4L, 4L, 3L, 2L, 4L, 5L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 5L,
1L, 5L, 3L, 4L, 3L, 5L, 4L, 4L, 1L, 2L, 3L, 3L, 5L, 2L, 4L, 4L,
2L, 5L, 2L, 2L, 3L, 3L, 5L, 3L, 2L, 2L, 2L, 2L, 5L, 2L, 2L, 4L,
3L, 2L, 5L, 4L, 5L, 3L, 2L, 4L, 3L, 5L, 2L, 5L, 3L, 5L, 2L, 1L,
2L, 3L, 5L, 3L, 2L, 3L, 5L, 4L, 5L, 5L, 4L, 4L, 5L, 4L, 2L, 5L,
2L, 2L, 3L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 3L, 2L, 5L, 2L, 2L, 4L, 2L, 3L, 2L, 2L, 4L, 1L, 4L, 2L, 3L,
2L, 2L, 2L, 3L, 4L, 3L, 4L, 2L, 2L, 3L, 2L, 4L, 2L, 2L, 3L, 5L,
4L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 4L, 2L, 2L, 5L, 2L,
3L, 2L, 4L, 3L, 4L, 3L, 2L, 5L, 3L, 4L, 2L, 5L, 2L, 5L, 2L, 2L,
3L, 2L, 3L, 2L, 4L, 2L, 2L, 2L, 5L, 2L, 4L, 2L, 5L, 4L, 2L, 2L,
4L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 2L, 4L, 4L, 2L, 4L, 5L,
5L, 3L, 4L, 2L, 2L, 2L, 5L, 3L, 2L, 3L, 2L, 2L, 1L, 4L, 2L, 2L,
2L, 2L, 3L, 1L, 3L, 2L, 1L, 2L, 4L, 2L, 3L, 2L, 5L, 1L, 3L, 2L,
1L, 3L, 5L, 2L, 1L, 2L, 3L, 2L, 4L, 2L, 2L, 2L, 2L, 3L, 2L, 2L,
1L, 5L, 2L, 2L, 4L, 2L, 3L, 2L, 4L, 3L, 5L, 2L, 2L, 3L, 5L, 5L,
3L, 4L, 3L, 2L, 2L, 5L, 1L, 2L, 2L, 3L, 3L, 4L, 2L, 2L, 4L, 3L,
2L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 4L, 4L, 5L, 4L, 2L, 1L, 2L,
2L, 4L, 5L, 2L, 4L, 4L, 3L, 2L, 2L, 4L, 5L, 2L, 4L, 2L, 5L, 5L,
2L, 2L, 1L, 2L, 3L, 4L, 4L, 4L, 4L, 2L, 3L, 4L, 2L, 5L, 3L, 4L,
2L, 4L, 1L, 4L, 1L, 3L, 4L, 3L, 1L, 4L, 1L, 4L, 2L, 3L, 2L, 2L,
3L, 4L, 4L, 2L, 4L, 1L, 4L, 4L, 2L, 5L, 1L, 5L, 2L, 3L, 2L, 1L,
4L, 3L, 2L, 2L, 4L, 3L, 1L, 4L, 4L, 2L, 3L, 5L, 1L, 3L, 4L, 4L,
1L, 5L, 5L, 2L, 2L, 5L, 5L, 3L, 4L, 1L, 5L, 3L, 5L, 4L, 4L, 3L,
4L, 5L, 2L, 4L, 2L, 3L, 3L, 3L, 2L, 3L, 4L, 2L, 4L, 1L, 2L, 1L,
3L, 2L, 4L, 2L, 2L, 4L, 3L, 3L, 2L, 2L, 4L, 4L, 2L, 4L, 2L, 4L,
3L, 3L, 4L, 3L, 3L, 4L, 4L, 5L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 5L, 2L, 4L, 4L, 5L, 4L, 4L, 4L, 4L, 2L, 2L, 5L, 2L, 4L,
5L, 4L, 3L, 5L, 4L, 5L, 2L, 3L, 4L, 2L, 2L, 2L, 3L, 4L, 4L, 5L,
3L, 4L, 2L, 5L, 4L, 4L, 3L, 2L, 2L, 5L, 3L, 5L, 2L, 4L, 1L, 4L,
4L, 3L, 3L, 2L, 5L, 5L, 5L, 4L, 2L, 3L, 1L, 2L, 2L, 3L, 4L, 5L,
4L, 3L, 2L, 2L, 3L, 4L, 3L, 3L, 5L, 2L, 3L, 4L, 2L, 4L, 2L, 2L,
4L, 4L, 2L, 3L, 5L, 3L, 2L, 4L, 4L, 5L, 1L, 4L, 1L, 2L, 1L, 2L,
4L, 5L, 2L, 5L, 2L, 5L, 4L, 2L, 3L, 2L, 3L, 2L, 5L, 5L, 3L, 3L,
4L, 4L, 2L, 4L, 4L, 2L, 5L, 2L, 5L, 5L, 5L, 5L, 2L, 3L, 4L, 2L,
1L, 2L, 4L, 4L, 4L, 2L, 4L, 2L, 5L, 4L, 3L, 2L, 5L, 3L, 5L, 4L,
2L, 2L, 2L, 1L, 2L, 2L, 3L, 3L, 5L, 4L, 1L, 4L, 1L, 4L, 2L, 4L,
5L, 4L, 4L, 3L, 2L, 3L, 3L, 5L, 2L, 3L, 4L, 3L, 5L, 3L, 1L, 3L,
4L, 2L, 4L, 2L, 5L, 5L, 1L, 4L, 3L, 1L, 2L, 2L, 3L, 5L, 5L, 3L,
4L, 5L, 1L, 1L, 4L, 2L, 4L), id = structure(c(2L, 1L, 4L, 4L,
1L, 4L, 3L, 1L, 1L, 4L, 1L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 1L, 4L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L,
4L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 1L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 1L, 4L, 4L, 4L, 1L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L,
2L, 3L, 4L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 3L, 1L, 4L, 4L, 4L, 4L, 1L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 4L,
4L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 1L, 4L, 3L, 4L, 2L, 4L,
4L, 4L, 3L, 2L, 4L, 2L, 3L, 2L, 1L, 1L, 3L, 4L, 4L, 4L, 2L, 4L,
3L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 1L, 4L,
4L, 4L, 2L, 4L, 3L, 3L, 4L, 2L, 1L, 4L, 3L, 4L, 4L, 4L, 2L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L,
3L, 4L, 1L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 1L, 3L, 1L, 4L, 2L, 3L,
4L, 4L, 3L, 1L, 3L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 4L, 4L, 1L, 4L,
4L, 2L, 4L, 4L, 2L, 4L, 2L, 4L, 1L, 3L, 4L, 3L, 4L, 4L, 4L, 3L,
4L, 4L, 4L, 4L, 3L, 3L, 1L, 2L, 4L, 2L, 4L, 4L, 2L, 2L, 1L, 2L,
4L, 4L, 3L, 3L, 2L, 4L, 4L, 2L, 1L, 2L, 4L, 4L, 1L, 1L, 4L, 4L,
4L, 4L, 4L, 4L, 3L, 4L, 3L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 1L, 4L,
3L, 4L, 4L, 4L, 4L, 4L, 1L, 2L, 4L, 1L, 3L, 3L, 2L, 1L, 2L, 4L,
2L, 2L, 4L, 3L, 4L, 1L, 4L, 2L, 4L, 2L, 2L, 2L, 4L, 3L, 4L, 4L,
3L, 1L, 1L, 4L, 4L, 3L, 1L, 4L, 3L, 3L, 3L, 4L, 3L, 2L, 4L, 3L,
1L, 4L, 3L, 4L, 4L, 4L, 2L, 2L, 2L, 4L, 1L, 1L, 2L, 1L, 4L, 1L,
3L, 4L, 4L, 1L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 2L, 3L, 4L, 4L, 4L,
4L, 2L, 1L, 4L, 4L, 4L, 2L, 4L, 4L, 1L, 4L, 1L, 4L, 2L, 2L, 3L,
3L, 1L, 1L, 2L, 3L, 4L, 1L, 2L, 2L, 4L, 3L, 4L, 2L, 4L, 2L, 3L,
4L, 1L, 4L, 4L, 2L, 3L, 4L, 1L, 3L, 3L, 1L, 2L, 3L, 1L, 2L, 4L,
4L, 4L, 4L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 4L, 1L, 4L, 3L, 1L, 3L,
3L, 3L, 3L, 2L, 4L, 4L, 2L, 4L, 2L, 3L, 3L, 3L, 1L, 2L, 2L, 2L,
4L, 2L, 3L, 1L, 4L, 3L, 4L, 2L, 4L, 1L, 4L, 2L, 2L, 3L, 1L, 4L,
3L, 1L, 1L, 2L, 2L, 3L, 1L, 4L, 3L, 4L, 1L, 1L, 1L, 4L, 3L, 4L,
1L, 2L, 4L, 3L, 2L, 4L, 3L, 1L, 2L, 2L, 3L, 3L, 2L, 4L, 1L, 4L,
2L, 3L, 4L, 2L, 4L, 1L, 4L, 2L, 2L, 3L, 4L, 2L, 1L, 3L, 1L, 3L,
3L, 1L, 1L, 3L, 2L, 1L, 4L, 3L, 2L, 4L, 4L, 3L, 3L, 3L, 3L, 4L,
3L, 3L, 1L, 4L, 3L, 1L, 3L, 1L, 3L, 2L, 4L, 4L, 2L, 4L, 1L, 2L,
1L, 1L, 2L, 1L, 1L, 2L, 1L, 4L, 4L, 2L, 1L, 4L, 3L, 3L, 3L, 3L,
3L, 4L, 3L, 4L, 2L, 1L, 1L, 4L, 2L, 2L, 2L, 4L, 3L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 1L, 3L, 2L, 3L, 4L, 1L, 3L, 4L,
3L, 2L, 2L, 1L, 2L, 2L, 3L, 4L, 1L, 1L, 4L, 4L, 4L, 1L, 2L, 4L,
4L, 4L, 4L, 3L, 1L, 1L, 1L, 1L, 4L, 1L, 2L, 3L, 1L, 1L, 1L, 4L,
2L, 3L, 4L, 2L, 2L, 3L, 3L, 4L, 4L, 4L, 2L, 1L, 4L, 2L, 2L, 3L,
2L, 2L, 3L, 3L, 4L, 2L, 1L, 4L, 1L, 3L, 3L, 1L, 3L, 1L, 1L, 1L,
4L, 4L, 1L, 3L, 3L, 2L, 4L, 2L, 3L, 3L, 4L, 4L, 4L, 3L, 4L, 1L,
1L, 1L, 2L, 3L, 1L, 4L, 4L, 1L, 2L, 4L, 1L, 1L, 3L, 2L, 1L, 2L,
3L, 2L, 1L, 1L, 1L, 2L, 2L, 4L, 2L, 2L, 4L, 1L, 4L, 4L, 4L, 1L,
1L, 3L, 4L, 1L, 2L, 4L, 2L, 1L, 2L, 2L, 3L, 1L, 2L, 4L, 4L, 4L,
4L, 2L, 2L, 2L, 2L, 3L, 1L, 1L, 2L, 2L, 4L, 1L, 2L, 2L, 2L, 2L,
2L, 3L, 1L, 4L, 2L, 1L, 1L, 2L, 2L, 2L, 4L, 1L, 3L, 1L, 3L, 4L,
3L, 4L, 1L, 1L, 3L, 2L, 2L, 4L, 2L, 3L, 3L, 3L, 2L, 4L, 3L, 2L,
4L, 1L, 3L, 4L, 2L, 2L, 3L, 3L, 3L, 2L, 1L, 3L, 2L, 1L, 4L, 3L,
1L, 1L, 1L, 2L, 4L, 2L, 1L, 4L, 1L, 2L, 4L, 1L, 4L, 1L, 4L, 2L,
3L, 3L, 2L, 1L, 4L, 4L, 3L, 4L, 3L, 2L, 2L, 2L, 3L, 1L, 1L, 1L,
4L, 2L, 1L, 3L, 3L, 3L, 4L, 3L, 1L, 4L, 1L, 3L, 1L, 2L, 4L, 1L,
3L, 2L, 2L, 4L, 1L, 2L, 2L, 4L, 3L, 1L, 4L, 1L, 1L, 3L, 1L, 1L,
3L, 2L, 1L, 1L, 4L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 1L,
1L, 4L, 3L, 4L, 1L, 3L, 3L, 3L, 2L, 1L, 3L, 3L, 2L, 2L, 1L, 4L,
4L, 3L, 1L, 3L, 2L, 4L, 1L, 4L, 1L, 4L, 1L, 1L, 2L, 3L, 4L, 3L,
2L, 3L, 4L, 4L, 1L, 2L, 3L, 3L, 3L, 2L, 1L, 4L, 1L, 3L, 1L, 1L,
2L, 2L, 1L, 4L, 3L, 1L, 3L, 2L, 1L, 3L, 1L, 4L, 1L, 3L, 2L, 4L,
1L, 1L, 3L, 3L), .Label = c("Anshin", "Cartman", "Chiarah", "Mucki"
), class = "factor"), md = c(8, 8, 2, 2, 2, 2, 2, 5.66, 2, 16,
1, 4, 1, 8, 1, 5.66, 2.83, 8, 16, 4, 8, 1, 16, 4, 2, 2.83, 1,
1, 8, 2.83, 2, 16, 8, 8, 5.66, 4, 4, 4, 2, 5.66, 16, 1, 5.66,
5.66, 16, 2.83, 5.66, 8, 2, 1, 5.66, 16, 2, 8, 8, 5.66, 5.66,
4, 8, 2, 16, 16, 1, 2, 8, 8, 2.83, 4, 8, 2.83, 16, 16, 5.66,
16, 8, 5.66, 8, 1, 5.66, 5.66, 8, 2, 1, 8, 16, 2, 16, 16, 8,
2.83, 4, 5.66, 4, 2.83, 1, 16, 2.83, 1, 8, 16, 16, 2, 16, 8,
16, 16, 2, 8, 16, 1, 1, 16, 8, 5.66, 2, 8, 2, 5.66, 2.83, 1,
5.66, 2, 5.66, 4, 4, 2, 2, 2.83, 2, 4, 4, 1, 8, 5.66, 2, 4, 4,
8, 2.83, 2, 4, 1, 4, 5.66, 1, 16, 1, 5.66, 2.83, 2.83, 4, 8,
8, 16, 4, 4, 2, 8, 1, 8, 2.83, 5.66, 2.83, 2.83, 1, 2, 5.66,
4, 5.66, 8, 1, 16, 5.66, 1, 2, 4, 2, 5.66, 16, 1, 5.66, 5.66,
2.83, 2.83, 2, 2, 2.83, 2.83, 2, 8, 4, 8, 2, 16, 2, 5.66, 16,
4, 2.83, 4, 5.66, 1, 2, 1, 4, 4, 8, 2, 1, 4, 2.83, 2, 5.66, 2,
2, 2.83, 8, 1, 4, 8, 4, 8, 8, 5.66, 4, 16, 2, 2.83, 1, 16, 2.83,
8, 1, 8, 4, 4, 1, 8, 2, 5.66, 8, 8, 4, 8, 1, 4, 2.83, 16, 16,
2, 1, 2, 16, 2, 16, 16, 8, 2.83, 16, 1, 8, 2, 1, 1, 1, 4, 4,
2, 16, 16, 2.83, 5.66, 4, 2.83, 8, 2, 5.66, 2, 1, 2.83, 4, 1,
4, 8, 8, 2, 1, 8, 2.83, 8, 2.83, 5.66, 4, 2.83, 5.66, 2.83, 1,
2, 8, 1, 2.83, 8, 2.83, 4, 5.66, 2.83, 2, 16, 2.83, 8, 4, 16,
4, 2.83, 16, 1, 2, 2.83, 16, 2, 16, 2.83, 16, 5.66, 4, 2.83,
1, 2, 8, 5.66, 2, 8, 16, 1, 2.83, 5.66, 1, 2, 4, 1, 2, 2, 16,
4, 2, 8, 1, 4, 5.66, 2, 4, 5.66, 1, 2, 2.83, 5.66, 8, 16, 2.83,
16, 2, 1, 4, 4, 2.83, 4, 4, 2, 16, 8, 8, 4, 8, 2, 8, 5.66, 16,
1, 1, 1, 4, 2.83, 2.83, 2, 2.83, 8, 1, 4, 16, 5.66, 4, 8, 1,
8, 4, 4, 16, 2.83, 1, 1, 8, 16, 5.66, 5.66, 16, 16, 2, 2, 5.66,
16, 2.83, 4, 5.66, 1, 8, 4, 2.83, 2, 2.83, 4, 2, 8, 1, 5.66,
1, 8, 1, 1, 16, 16, 4, 16, 4, 2, 2.83, 4, 4, 5.66, 5.66, 16,
4, 2, 8, 8, 8, 1, 8, 5.66, 5.66, 16, 16, 1, 2, 2, 16, 1, 4, 1,
1, 5.66, 5.66, 2, 4, 16, 1, 1, 4, 16, 2, 1, 2.83, 1, 2, 4, 4,
2, 2, 16, 2, 16, 1, 4, 2.83, 5.66, 8, 16, 2, 1, 16, 2, 2, 4,
5.66, 2, 1, 1, 8, 16, 2, 8, 4, 2, 8, 1, 2, 2, 2.83, 2.83, 8,
2, 2.83, 2.83, 2, 2.83, 1, 5.66, 2.83, 5.66, 8, 8, 8, 1, 1, 16,
1, 2.83, 5.66, 8, 16, 5.66, 2, 5.66, 5.66, 2, 1, 5.66, 8, 2.83,
16, 2.83, 1, 16, 16, 4, 4, 2.83, 5.66, 16, 16, 2.83, 16, 8, 4,
2.83, 16, 8, 8, 5.66, 2, 2.83, 5.66, 8, 1, 5.66, 8, 2.83, 5.66,
8, 2, 4, 5.66, 8, 16, 1, 16, 4, 2, 16, 2.83, 2.83, 4, 5.66, 4,
1, 16, 2, 5.66, 1, 2.83, 5.66, 2, 2, 5.66, 8, 5.66, 1, 1, 2,
4, 5.66, 2, 4, 1, 5.66, 16, 1, 8, 2.83, 4, 16, 2, 16, 16, 8,
1, 4, 4, 5.66, 1, 4, 1, 4, 1, 5.66, 1, 5.66, 4, 1, 1, 16, 5.66,
1, 1, 5.66, 4, 8, 4, 2, 2, 2, 1, 4, 5.66, 2, 5.66, 2.83, 4, 5.66,
5.66, 16, 4, 5.66, 4, 8, 2.83, 16, 1, 5.66, 8, 5.66, 16, 4, 16,
2, 2.83, 2, 1, 2.83, 1, 5.66, 2.83, 2, 1, 2.83, 4, 16, 2, 16,
2, 2.83, 1, 16, 4, 2.83, 5.66, 2.83, 1, 5.66, 8, 4, 8, 2, 2,
1, 2, 4, 5.66, 16, 2.83, 16, 16, 2, 5.66, 2, 8, 16, 2, 8, 16,
2.83, 16, 2, 8, 1, 5.66, 1, 5.66, 5.66, 16, 1, 16, 16, 1, 2,
5.66, 16, 1, 2, 5.66, 2.83, 1, 16, 5.66, 1, 1, 2.83, 1, 4, 4,
2, 1, 2, 2.83, 4, 5.66, 2.83, 2, 2.83, 1, 1, 1, 1, 2, 16, 8,
4, 4, 16, 5.66, 5.66, 1, 4, 5.66, 2.83, 5.66, 8, 1, 1, 2, 1,
2.83, 1, 2, 8, 16, 5.66, 8, 4, 5.66, 4, 1, 1, 2, 16, 8, 4, 4,
2.83, 4, 8, 16, 16, 4, 5.66, 5.66, 4, 8, 2, 4, 5.66, 1, 2, 5.66,
8, 16, 2.83, 2, 1, 5.66, 1, 2.83, 5.66, 2.83, 16, 16, 2, 2, 16,
16, 1, 1, 5.66, 2.83, 1, 16, 2, 1, 2, 1, 4, 16, 5.66, 5.66, 1,
16, 5.66, 2, 16, 1, 16, 1, 1, 8, 16, 5.66, 5.66, 5.66, 16, 16,
5.66, 5.66, 5.66, 4, 1, 8, 4, 5.66, 1, 8, 2, 8, 2, 5.66, 4, 16,
5.66, 5.66, 2.83, 5.66, 8, 8, 1, 16, 16, 2, 4, 8, 5.66, 2, 5.66,
16, 2, 4, 16, 8, 1, 2.83, 1, 1, 2.83, 1, 8, 2, 16, 1, 4, 8, 5.66,
1, 8, 16, 2, 4, 16, 5.66, 2.83, 4, 8, 4, 4, 16, 16, 2.83, 8,
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-1000L))
(см. https://stats.stackexchange.com/questions/254361/modeling-reaction-time-with-glmer для объяснения, почему именно это распределение для данных времени отклика. Оригинал статьи здесь: https://doi.org/10.3389/fpsyg.2015.01171)