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在 glmer 中使用逆高斯分布时出错

[英]Error using inverse gaussian distribution with glmer

 原文  2023-01-19 00:29:14  8   1    r

问题描述

I'm trying to fit a model and even after searching through my other forums, I can't for the life of me figure out what is wrong.我正在尝试安装 model，甚至在搜索了我的其他论坛之后，我终究无法找出问题所在。

Here's a histogram to show why I'm using the inverse.gaussian family.这是一个直方图，用于显示我为什么使用 inverse.gaussian 系列。

在此处输入图像描述

Here is my code for fitting the model:这是我用于拟合 model 的代码：

glm.full.odba  <- glmer(meanodba ~ AirTemp + LagAir + Radiation + Windspeed + LagRadiation + 
        + Precip + Raining + LULC + Elevation + (1 | Turtle),
      data = na.omit(odba_fit_data_set), 
      family = inverse.gaussian(link='inverse'))

Here is my data.这是我的数据。

> 
> dput(odba_fit_data_set[150:300,])
structure(list(Turtle = c("R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", "R3L1", "R3L12", 
"R3L1", "R3L12"), LULC = c(41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 81L, 41L, 81L, 41L, 81L, 41L, 81L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 
41L), meanodba = c(NA, NA, NA, 0.0024429845, 0.0024429845, 0.002844277, 
0.002844277, 0.0701741105, 0.0701741105, 0.003012713, 0.003012713, 
0.168142569, 0.168142569, 0.19269525, 0.19269525, 0.003600107, 
0.003600107, 0.003282639, 0.003282639, 0.006676893, 0.006676893, 
0.004318509, 0.004318509, 0.0049651105, 0.0049651105, 0.052186496, 
0.052186496, 0.002547072, 0.002547072, 0.003099685, 0.003099685, 
0.006663461, 0.006663461, 0.002233525, 0.002233525, 0.002393341, 
0.002393341, 0.003468077, 0.003468077, 0.001722613, 0.001722613, 
0.002360538, 0.002360538, 0.006206355, 0.006206355, 0.002143561, 
0.002143561, 0.001891434, 0.001891434, 0.00230823, 0.00230823, 
0.002935105, 0.002935105, 0.00518635, 0.00518635, 0.016733862, 
0.016733862, 0.002794176, 0.002794176, 0.0095226515, 0.0095226515, 
0.002396399, 0.002396399, 0.002252792, 0.002252792, 0.034889546, 
0.034889546, 0.001938629, 0.001938629, 0.002258683, 0.002258683, 
0.001835079, 0.001835079, 0.002609543, 0.002609543, 0.0026749535, 
0.0026749535, 0.004785412, 0.004785412, 0.0476675725, 0.0476675725, 
0.002130554, 0.002130554, 0.020104818, 0.020104818, 0.002233463, 
0.002233463, 0.00265004, 0.00265004, 0.002577044, 0.002577044, 
0.001952181, 0.001952181, 0.002061738, 0.002061738, 0.002173133, 
0.002173133, 0.002588346, 0.002588346, 0.001712986, 0.001712986, 
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, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA), Elevation = c(NA, NA, NA, 282.27, 283.96, 282.27, 283.96, 
282.27, 283.96, 282.27, 283.96, 283.21, 284.28, 283.21, 284.28, 
283.21, 284.28, 283.21, 284.28, 282.14, 283.96, 282.14, 283.96, 
282.14, 283.96, 282.14, 283.96, 281.63, 284.46, 281.63, 284.46, 
281.63, 284.46, 281.63, 284.46, 281.63, 284.22, 281.63, 284.22, 
281.63, 284.22, 281.63, 284.22, 281.63, 284.22, 281.63, 284.22, 
281.63, 284.22, 281.63, 284.22, 282.63, 284.28, 282.63, 284.28, 
282.63, 284.28, 282.63, 284.28, 281.63, 284.6, 281.63, 284.6, 
281.63, 284.6, 281.63, 284.6, 282.14, 284.4, 282.14, 284.4, 282.14, 
284.4, 282.14, 284.4, 281.63, 284.4, 281.63, 284.4, 281.63, 284.4, 
281.63, 284.4, 282.14, 284.4, 282.14, 284.4, 282.14, 284.4, 282.14, 
284.4, 281.36, 284.28, 281.36, 284.28, 281.36, 284.28, 281.36, 
284.28, 282.14, 284.4, 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, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA), Radiation = c(-0.597405546493466, 
-0.301272695347495, -0.302040941158138, -0.0681408493951469, 
-0.0727447343846593, 0.398122842509549, 0.385847679162298, 0.078060477727512, 
0.0710511918970137, 0.0108868949954796, 0.00498279333516397, 
0.117574349922825, 0.109914955756925, 0.0701577032884494, 0.0632784391250314, 
0.283532613143141, 0.273142763968554, 1.00268508709784, 0.980463266218946, 
1.23186554583066, 1.20587309660643, 1.01453924875644, 0.992122395376919, 
0.836726823877526, 0.817235458007317, 0.797212951682213, 0.778371694147405, 
0.342803421436111, 0.331438409758422, 0.330949259777517, 0.319779280600448, 
1.19235167363534, 1.16700933274652, 0.824872662218932, 0.805576328849343, 
0.354657583094705, 0.343097538916395, 0.8209212749994, 0.801689952463352, 
2.40147616281193, 2.35624050685982, 2.75710101256975, 2.70601438159902, 
2.26712899734786, 2.22410370973612, 2.65436494486193, 2.60496859556325, 
2.37381645227521, 2.32903587215788, 2.21180957627443, 2.16969444033224, 
1.46499739178301, 1.43516930337991, 2.12092767022521, 2.08030778345444, 
1.85618472651661, 1.81992056559304, 2.17624709129864, 2.13471705285832, 
2.16834431685958, 2.12694430008634, 2.3856706139338, 2.34069500131585, 
2.19995541461583, 2.15803531117427, 1.86013611373614, 1.82380694197903, 
2.32639980564083, 2.28239935552598, 2.14068460632286, 2.0997396653844, 
2.22366373793302, 2.18135356949022, 2.11697628300567, 2.07642140706845, 
1.88779582427286, 1.85101157668097, 1.71788617383301, 1.68389739208335, 
1.5400737489541, 1.50901045471374, 1.41758074514863, 1.38853278674802, 
1.23186554583066, 1.20587309660643, 1.04219895929315, 1.01932703007886, 
0.864386534414245, 0.844440092709255, 0.67076856065721, 0.654007649795688, 
0.413928391387674, 0.401393184706263, 0.0741090905079807, 0.0671648155110226, 
-0.0246755899803023, -0.0299945941387565, -0.210390789298274, 
-0.212654284280341, -0.234099112615462, -0.235972542596288, -0.522550379641249, 
-0.519678018773643, -0.609480898470938, -0.605178299265449, -0.668751706763908, 
-0.663473945055316, -0.716168353398284, -0.71011046168721, -0.739876676715471, 
-0.733428720003157, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148), LagRadiation = c(-0.64404206312536, -0.601578124031875, 
-0.597405546493466, -0.301272695347495, -0.302040941158138, -0.0681408493951469, 
-0.0727447343846593, 0.398122842509549, 0.385847679162298, 0.078060477727512, 
0.0710511918970137, 0.0108868949954796, 0.00498279333516397, 
0.117574349922825, 0.109914955756925, 0.0701577032884494, 0.0632784391250314, 
0.283532613143141, 0.273142763968554, 1.00268508709784, 0.980463266218946, 
1.23186554583066, 1.20587309660643, 1.01453924875644, 0.992122395376919, 
0.836726823877526, 0.817235458007317, 0.797212951682213, 0.778371694147405, 
0.342803421436111, 0.331438409758422, 0.330949259777517, 0.319779280600448, 
1.19235167363534, 1.16700933274652, 0.824872662218932, 0.805576328849343, 
0.354657583094705, 0.343097538916395, 0.8209212749994, 0.801689952463352, 
2.40147616281193, 2.35624050685982, 2.75710101256975, 2.70601438159902, 
2.26712899734786, 2.22410370973612, 2.65436494486193, 2.60496859556325, 
2.37381645227521, 2.32903587215788, 2.21180957627443, 2.16969444033224, 
1.46499739178301, 1.43516930337991, 2.12092767022521, 2.08030778345444, 
1.85618472651661, 1.81992056559304, 2.17624709129864, 2.13471705285832, 
2.16834431685958, 2.12694430008634, 2.3856706139338, 2.34069500131585, 
2.19995541461583, 2.15803531117427, 1.86013611373614, 1.82380694197903, 
2.32639980564083, 2.28239935552598, 2.14068460632286, 2.0997396653844, 
2.22366373793302, 2.18135356949022, 2.11697628300567, 2.07642140706845, 
1.88779582427286, 1.85101157668097, 1.71788617383301, 1.68389739208335, 
1.5400737489541, 1.50901045471374, 1.41758074514863, 1.38853278674802, 
1.23186554583066, 1.20587309660643, 1.04219895929315, 1.01932703007886, 
0.864386534414245, 0.844440092709255, 0.67076856065721, 0.654007649795688, 
0.413928391387674, 0.401393184706263, 0.0741090905079807, 0.0671648155110226, 
-0.0246755899803023, -0.0299945941387565, -0.210390789298274, 
-0.212654284280341, -0.234099112615462, -0.235972542596288, -0.522550379641249, 
-0.519678018773643, -0.609480898470938, -0.605178299265449, -0.668751706763908, 
-0.663473945055316, -0.716168353398284, -0.71011046168721, -0.739876676715471, 
-0.733428720003157, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148, -0.743828063935003, 
-0.737315096389148, -0.743828063935003, -0.737315096389148), 
    AirTemp = c(-1.06888515955184, -0.884644073243182, -0.826648603212786, 
    -0.640333340558809, -0.586334559225632, -0.511337273701461, 
    -0.459448744000414, -0.411658494766236, -0.361400614053654, 
    -0.439021296826886, -0.388315786980216, -0.397977093735911, 
    -0.347943027590374, -0.333479060307237, -0.284500119977765, 
    -0.268981026878563, -0.221057212365156, -0.0539875821163153, 
    -0.00958085365646016, 0.211822495044282, 0.251880826201564, 
    0.342773047763106, 0.380689153778679, 0.479587058066354, 
    0.515265018411486, 0.50890434598848, 0.544102703689945, 0.585129294586003, 
    0.619080685413937, 0.551903034940929, 0.586397975431684, 
    0.540176119772079, 0.5748629013203, 0.608583124923703, 0.642150833636704, 
    0.46590565703603, 0.501807431948205, 0.546039577356504, 0.580630438375992, 
    0.669172186629427, 0.701748716545518, 0.911528433452325, 
    0.940140248180776, 1.0307520710023, 1.05741350164651, 1.08743216098507, 
    1.11316635985153, 1.19688336922767, 1.22082705155777, 1.21447374198095, 
    1.23812966272485, 1.24379102990307, 1.26696734800331, 1.2496544874875, 
    1.272734885059, 1.29265317643995, 1.31503015680074, 1.37278709676042, 
    1.39385316322852, 1.36106018159157, 1.38231808911714, 1.49201073431039, 
    1.51112641669426, 1.48223830500302, 1.50151385493477, 1.52132802223252, 
    1.53996410197271, 1.53891839498579, 1.55726671313979, 1.55455428187759, 
    1.57264681195497, 1.60341642841447, 1.6207096207524, 1.64055165978249, 
    1.65723735543845, 1.61905231530627, 1.63608971956758, 1.62296128702922, 
    1.63993474427137, 1.62882474461364, 1.64570228132706, 1.62491577289069, 
    1.64185725662327, 1.66205100425872, 1.67838499130932, 1.62882474461364, 
    1.64570228132706, 1.61514334358332, 1.63224469486378, 1.57214465463087, 
    1.58994942312204, 1.55455428187759, 1.57264681195497, 1.49982867775629, 
    1.51881646610184, 1.43337615846614, 1.45345104613734, 1.36887812503747, 
    1.39000813852473, 1.33956083711535, 1.36117045324627, 1.27897177540962, 
    1.30157257033746, 1.16561159544407, 1.19006685392742, 1.08156870340065, 
    1.10739882279584, 1.01707066997197, 1.04395591518323, 0.946709178958875, 
    0.974745470514926, 0.866575258638401, 0.895922464087139, 
    0.811849654517101, 0.842092118234016, 0.749306106949902, 
    0.780571722973305, 0.590992752170428, 0.624848222469629, 
    0.557766492525354, 0.592165512487376, 0.497177430819629, 
    0.532567629578561, 0.448315284282755, 0.48450482078113, 0.356454448793431, 
    0.39414674024196, 0.248957726412307, 0.288408560887612, 0.176641749537732, 
    0.217275603867414, 0.118007173693484, 0.159600233310497, 
    0.317364731563931, 0.355696493204016, 0.307592302256556, 
    0.346083931444529, 0.260684641581156, 0.299943634998995, 
    0.250912212273782, 0.290331073239509, 0.247003240550832, 
    0.286486048535714, 0.260684641581156, 0.299943634998995, 
    0.290001929503282, 0.328781320277454, 0.270457070888531, 
    0.309556196758481, 0.282183986057382, 0.321091270869865), 
    LagAir = c(-1.15111030880199, -1.13781139154986, -1.07614378044101, 
    -0.89150203046162, -0.833944227274796, -0.647147505572498, 
    -0.5936668927845, -0.518128316431041, -0.466800460173624, 
    -0.418431670276279, -0.368767307701583, -0.445799377063861, 
    -0.395678369164496, -0.404747816882488, -0.355311776970126, 
    -0.34023822231176, -0.291878560664688, -0.275728627741031, 
    -0.22844534435925, -0.0606966458386043, -0.0170012900077894, 
    0.205161077240761, 0.244420449917653, 0.336135102581331, 
    0.373209101204452, 0.472973636519239, 0.507764408519017, 
    0.502296179505934, 0.536597688657853, -1.30006279607623, 
    -1.23568793054257, 0.545302575886419, 0.578886499528145, 
    0.533573558691741, 0.567353187472611, 0.601992825660695, 
    0.634630841129894, 0.459289783125448, 0.494308877787561, 
    0.53943806728908, 0.573119843500378, 0.662592747833198, 0.694219620083487, 
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    1.36633377951387, 1.38621834341554, 1.35460476231919, 1.37468503136001, 
    1.48557878765976, 1.5034736826468, 1.4758046066642, 1.49386258926719, 
    1.51490133064646, 1.53230696278564, 1.53249485643847, 1.54960693086894, 
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    1.63414633879235, 1.6495623020169, 1.61264314060211, 1.62841789658176, 
    1.61655281300033, 1.6322623339336, 1.62241732159767, 1.63802898996137, 
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    0.28335452520528, 0.321309196954548, 0.26380616321415, 0.302087010195324
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    0.945984985363425, 1.0151761550004, 1.01407868013798, 1.24689420630329, 
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    1.40722340845897, 1.19618582388521, 1.19523360397216, 1.24881984107866, 
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    0.354683427048396, 0.353055926147278, 0.242996610076919, 
    0.241279483781504, 0.232726557941611, 0.231001190230628), 
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    1.22157173119628, 1.32835782958882, 1.32756663343969, 1.36815100076617, 
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    0.378109266677538, 0.155101105198786, 0.15327159525213, -0.455916619975895, 
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    0.143635695048184, 0.146757375758375, 0.144920481742044, 
    0.354708786427069, 0.353055926147278, 0.243031176993881, 
    0.241279483781504), Precip = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0), Raining = c(FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
    FALSE, FALSE, FALSE, FALSE), LogBT = c(2.64513406688667, 
    2.59256452449451, 2.64219525830619, 2.69063272706514, 2.64811145513026, 
    2.6095794764782, 2.63769926500569, 2.63385333610875, 2.64219525830619, 
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    2.8462844070338, 2.69856087508109, 3.00284028501337, 2.75059870434817, 
    2.84991620857235, 2.7235297719506, 2.87139656595869, 2.73579506141077, 
    2.9861700340503, 2.75191821844772, 3.13182081056284, 2.83493734730432, 
    3.12176268737869, 2.79620351842232, 3.14357740081797, 2.82510210534962, 
    3.1453584475098, 2.84227024544059, 3.14087103922023, 2.89674032434704, 
    3.13091854610906, 2.87929208587355, 3.12544388007565, 2.8863079562727, 
    3.1480527080751, 2.90361698464619, 3.28571170505446, 2.9472595589921, 
    3.14537279790336, 2.91838315712639, 3.18838912559666, 2.93071363717954, 
    3.28182558459247, 2.94946143322156, 3.44722181997343, 3.3078264314472, 
    3.42035710081212, 3.07551340855884, 3.46366083466759, 3.24665958987969, 
    3.47661402094691, 3.37641504282428, 3.38502283159387, 3.41270864983416, 
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    2.96382872454098, 3.11237391732968, 2.94313989010148, 3.06194127366433, 
    2.95298133648636, 3.08317827830151, 2.94753943095251, 3.06972595346232, 
    2.9420677489683, 3.05704685337308, 2.91303883356946, 3.011933652892, 
    2.92652509339029, 3.03122810923883, 2.91980469820808, 3.01907438112691, 
    2.90962957450058, 3.00780905477944, 2.88080764874609, 2.97213947261567, 
    2.89244368404806, 2.98801927134683, 2.88429779310769, 2.97958595381129, 
    2.87728651834751, 2.97000412498126, 2.85353486784419, 2.93847385471371, 
    2.86191512581965, 2.95162363392793, 2.85591449628676, 2.94398273475191, 
    2.85111104394286, 2.93513265142506, 2.83409530795287, 2.90817529320446, 
    2.84022790011906, 2.92064946742964, 2.83656067665874, 2.91273102705058, 
    2.83162384617939, 2.90591696923163, 2.81929337991819, 2.88861094932297, 
    2.82547761797817, 2.89558039160355)), row.names = 150:300, class = "data.frame")

And lastly, here is the error I get.最后，这是我得到的错误。

Error in (function (fr, X, reTrms, family, nAGQ = 1L, verbose = 0L, maxit = 100L,  : 
  PIRLS loop resulted in NaN value

I'm really struggling here.我真的在这里挣扎。 If someone could propose a simple answer to fix this that would be incredible.如果有人可以提出一个简单的答案来解决这个问题，那将是不可思议的。

1 个解决方案

解决方案1
 0  2023-01-19 02:13:00

Can't solve it (yet), but here's what I've tried so far.无法解决它（还），但这是我到目前为止所尝试过的。

Even when I take out the two variables that have no variability in the sample you gave us, and even when I simplify the problem by using glm() (without the random effect), I get an error:即使我在你给我们的样本中取出两个没有可变性的变量，甚至当我通过使用glm() （没有随机效应）简化问题时，我也会收到一个错误：

(I called your data above dd ) （我在dd上面调用了你的数据）

mf <- model.frame( meanodba ~ AirTemp + LagAir + Radiation +
                   Windspeed + LagRadiation + 
                   Precip + Raining + LULC + Elevation, dd)
bad <- sapply(mf, function(x) length(unique(x))==1)
glm1  <- glm(meanodba ~ .,
             data = mf[!bad],
             family = inverse.gaussian(link='inverse'))

Error in glm.fit(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, : NA/NaN/Inf in 'x' glm.fit(x = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, : NA/NaN/Inf in ' X'
In addition: Warning message: In sqrt((weights[good] * mu.eta.val[good]^2)/variance(mu)[good]): NaNs produced另外：警告信息：In sqrt((weights[good] * mu.eta.val[good]^2)/variance(mu)[good]): NaNs produced

In this data set ( pairs(mf[,bad], gap = 0) ) the values for LULC and Elevation are very sparse (only two unique values, one of which is rare), but removing these two variables doesn't help either.在此数据集中 ( pairs(mf[,bad], gap = 0) ) LULC和Elevation的值非常稀疏（只有两个唯一值，其中一个很少见），但是删除这两个变量也无济于事.

在此处输入图像描述

Fitting with Gamma(link="log") works, but Gamma(link="inverse") doesn't.使用Gamma(link="log")拟合有效，但Gamma(link="inverse")无效。 Switching to inverse.gaussian(link="log") doesn't work either ("Error: inner loop 1; cannot correct step size In addition: Warning messages: 1: step size truncated due to divergence 2: step size truncated due to divergence")切换到inverse.gaussian(link="log")也不起作用（“错误：内循环 1；无法更正步长此外：警告消息：1：步长因发散而被截断 2：步长因发散而被截断分歧”）

I'm not surprised that the inverse link function is unstable/problematic, but I don't really understand why the inverse Gaussian would be.我对反向链接 function 不稳定/有问题并不感到惊讶，但我真的不明白为什么反向高斯会这样。

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