R 3.3.2 : Mac OS X에서 lme4 + lmer 테스트 문제

lme4 및 lmerTest를 사용할 때 Mac OS 버전의 R 3.3.2 (및 .3도!)에 영향을주는 문제를 발견했습니다.R 3.3.2 : Mac OS X에서 lme4 + lmer 테스트 문제

lmerTest 오류가 발생합니다 :

Error in calculation of the Satterthwaite's approximation. The output of lme4 package is returned summary from lme4 is returned some computational error has occurred in lmerTest

문제는되지 는 맥 OS에서 R 3.2 및 Windows 아래의 모든 R 버전으로 등장한다. 그러나이 문제는 설치 문제가 아닙니다. R을 다시 설치하고 다른 Mac에서도 오류를 재현했기 때문입니다. 다음과 같이

library(lme4) 

#' start of data creation 

mydat <- 
    structure(list(ID = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
         13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29, 
         1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
         20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 6, 7, 
         8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 
         24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
         13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 
         29, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 
         18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 1, 2, 3, 4, 5, 
         6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
         23, 24, 25, 26, 27, 28, 29), sex = c(1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ROI = structure(c(4L, 
         4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
         4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 
         1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
         1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
         3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
         3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
         2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
         2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
         5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 
         6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
         6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label = c("calf", 
         "DSCAT", "KM", "neck", "SSCAT", "VAT"), class = "factor"), 
         value = c(0.674, 
         0.561, 0.543, 0.563, 0.697, 0.608, 0.56, 0.448, 0.626, 0.515, 
         0.568, 0.528, 0.587, 0.532, 0.547, 0.514, 0.587, 0.572, 0.559, 
         0.569, 0.462, 0.531, 0.477, 0.582, 0.583, 0.569, 0.563, 0.576, 
         0.84, 0.638, 0.69, 0.707, 0.704, 0.627, 0.769, 0.637, 0.515, 
         0.669, 0.699, 0.626, 0.59, 0.639, 0.501, 0.632, 0.624, 0.641, 
         0.669, 0.656, 0.556, 0.569, 0.633, 0.608, 0.616, 0.664, 0.666, 
         0.669, 0.545, 0.514, 0.45, 0.585, 0.547, 0.572, 0.577, 0.458, 
         0.47, 0.537, 0.532, 0.455, 0.62, 0.501, 0.506, 0.44, 0.499, 0.577, 
         0.457, 0.481, 0.522, 0.516, 0.513, 0.559, 0.571, 0.515, 0.575, 
         0.521, 0.44, 0.637, 0.521, 0.634, 0.552, 0.581, 0.55, 0.553, 
         0.522, 0.634, 0.631, 0.512, 0.603, 0.593, 0.58, 0.442, 0.53, 
         0.463, 0.587, 0.538, 0.48, 0.557, 0.482, 0.53, 0.592, 0.445, 
         0.526, 0.45, 0.551, 0.51, 0.678, 0.64, 0.599, 0.589, 0.627, 0.621, 
         0.601, 0.526, 0.619, 0.599, 0.668, 0.615, 0.621, 0.561, 0.532, 
         0.56, 0.578, 0.686, 0.57, 0.457, 0.563, 0.61, 0.513, 0.638, 0.594, 
         0.777, 0.562, 0.663, 0.538, 0.471, 0.518, 0.47, 0.535, 0.644, 
         0.605, 0.474, 0.468, 0.563, 0.539, 0.47, 0.538, 0.453, 0.494, 
         0.576, 0.418, 0.609, 0.528, 0.453, 0.569, 0.484, 0.486, 0.558, 
         0.621, 0.465, 0.691, 0.398, 0.539, 0.574), Alter = c(45, 47, 
        51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 29, 50, 
        45, 61, 61, 58, 32, 27, 49, 45, 64, 28, 45, 47, 51, 44, 35, 26, 
        60, 44, 50, 42, 51, 57, 23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 
        27, 49, 27, 45, 64, 28, 45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 
        42, 51, 57, 23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 
        45, 64, 28, 45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 
        23, 26, 29, 29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 45, 64, 28, 
        45, 47, 51, 44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 
        29, 50, 45, 61, 61, 58, 32, 27, 49, 27, 45, 64, 28, 45, 47, 51, 
        44, 35, 26, 60, 44, 42, 50, 42, 51, 57, 23, 26, 29, 29, 50, 45, 
        61, 61, 58, 32, 27, 49, 27, 45, 64, 28), 
         BMI = c(29.7506923675537, 
        28.8, 28.8385677337646, 41.48, 27.7186069488525, 29.54, 38.06, 
        35.8453826904297, 35.57, 31.77, 31.75, 32.78, 30.5336246490479, 
        29.1074104309082, 36.4690246582031, 31.7769088745117, 31.5393238067627, 
        31.5596752166748, 27.593786239624, 30.8192825317383, 27.0799140930176, 
        31.481481552124, 29.0328979492188, 24.52, 29.4029197692871, 35.6112785339355, 
        28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
        41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 31.77, 
        31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
        31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
        30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
        24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
        28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
        41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
        31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
        31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
        30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
        24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
        28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
        41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
        31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
        31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
        30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
        24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
        28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
        41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
        31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
        31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
        30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
        24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
        28.2401905059814, 28.8979587554932, 29.7506923675537, 28.8, 28.8385677337646, 
        41.48, 27.7186069488525, 29.54, 38.06, 35.8453826904297, 35.57, 
        31.77, 31.75, 32.78, 30.5336246490479, 29.1074104309082, 36.4690246582031, 
        31.7769088745117, 31.5393238067627, 31.5596752166748, 27.593786239624, 
        30.8192825317383, 27.0799140930176, 31.481481552124, 29.0328979492188, 
        24.52, 29.4029197692871, 23.0956573486328, 35.6112785339355, 
        28.2401905059814, 28.8979587554932)), .Names = c("ID", "sex", 
        "ROI", "value", "Alter", "BMI"), row.names = c(NA, -172L), class = c("tbl_df","tbl", "data.frame")) 

#' end of data creation 


library(lmerTest) 
mod <- lmer(value~Alter+ROI+BMI+(1|ID),data=mydat,REML=F) 
summary(mod) 
sessionInfo()

시스템 정보는 다음과 같습니다 : 여기

은 예제 코드입니다

이

R version 3.3.3 (2017-03-06) 
Platform: x86_64-apple-darwin13.4.0 (64-bit) 
Running under: macOS Sierra 10.12.3 

locale: 
[1] C 

attached base packages: 
[1] stats  graphics grDevices utils  datasets methods base  

other attached packages: 
[1] lmerTest_2.0-33 lme4_1.1-12  Matrix_1.2-8 

loaded via a namespace (and not attached): 
[1] Rcpp_0.12.9   Formula_1.2-1  knitr_1.15.1  magrittr_1.5   cluster_2.0.5  splines_3.3.3  MASS_7.3-45   munsell_0.4.3 [9] colorspace_1.3-2 lattice_0.20-34  minqa_1.2.4   stringr_1.1.0  plyr_1.8.4   tools_3.3.3   nnet_7.3-12   grid_3.3.3 [17] data.table_1.10.0 checkmate_1.8.2  htmlTable_1.8  gtable_0.2.0  nlme_3.1-131  latticeExtra_0.6-28 htmltools_0.3.5  digest_0.6.11 [25] survival_2.40-1  lazyeval_0.2.0  assertthat_0.1  tibble_1.2   gridExtra_2.2.1  RColorBrewer_1.1-2 nloptr_1.0.4  ggplot2_2.2.1 [33] base64enc_0.1-3  acepack_1.4.1  rpart_4.1-10  stringi_1.1.2  backports_1.0.4  scales_0.4.1  Hmisc_4.0-2   foreign_0.8-67

출처

2017-03-09 user98678

나는 최근 "일부 전산 오류가 lmerTest 발생했습니다"그리고 나는 그들 중 적어도 일부는 여기에보고 된 문제와 관련되었을 수 있습니다 것으로 나타났습니다 많이 했어 : https://stackoverflow.com/questions/42805643/lmertestanova-uses-lazy-loading-of-data-sets – mmagnuski

이 정말 대답은 아니지만 코멘트에 대한 긴 약간의 ...

나는 이러한 환경 중 하나에서이를 복제 할 수 없습니다

R version 3.3.2 (2016-10-31) 
Platform: x86_64-apple-darwin13.4.0 (64-bit) 
Running under: OS X El Capitan 10.11.6 
[1] lmerTest_2.0-33 lme4_1.1-12  Matrix_1.2-8 
(also tried with Matrix 1.2-7) 

R Under development (unstable) (2017-02-13 r72168) 
Platform: x86_64-pc-linux-gnu (64-bit) 
Running under: Ubuntu 14.04.5 LTS 
lmerTest_2.0-33 lme4_1.1-13  Matrix_1.2-8

복제 가능성이 없으면 문제를 해결하기가 매우 어렵습니다. 그것이 시에라에게 특이하다고 믿기는 조금 힘들지만, 이상한 일들이 일어났습니다.

은 내가 추측 걸릴 것 당신이 모두 비록 증상 [사고] 및 의심 플랫폼 [ 이 (here 설명 된대로) 버전 1.2-7에 Matrix 패키지를 다운 그레이드 시도 할 것을 제안하고있어 32 비트 OS ] 다르다.

또는 here의 설명에 따라 lmerTest의 용기를 파고들 수 있습니다. 특정 상황이 다르기는하지만 (모델 적합은 단수가 아닙니다.) 계속 진행되고 있습니다. 내 시스템이 변경되지 않지만

CRAN이 check packages under 64-bit Sierra을 수행하지만 반복 시도 후 checks for lmerTest (및 lme4에 대한)이 플랫폼에 오류가 표시되지 않는 ...

출처

2017-03-10 23:29:39

, 코드, R3.3.3에서 일했다. 내가 꿈꿔 왔니? 초자연적 인 종류 ... 나는 의아해한다. 귀찮게해서 미안해.

R version 3.3.3 (2017-03-06) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: macOS Sierra 10.12.3

locale: [1] C

attached base packages: [1] stats graphics grDevices utils
datasets methods base

other attached packages: [1] lmerTest_2.0-33 lme4_1.1-12
Matrix_1.2-8

loaded via a namespace (and not attached): [1] Rcpp_0.12.9
nloptr_1.0.4 RColorBrewer_1.1-2 plyr_1.8.4
base64enc_0.1-3 tools_3.3.3 rpart_4.1-10
digest_0.6.12 [9] tibble_1.2 nlme_3.1-131
gtable_0.2.0 htmlTable_1.9 checkmate_1.8.2
lattice_0.20-34 gridExtra_2.2.1 stringr_1.2.0 [17] cluster_2.0.5 knitr_1.15.1 htmlwidgets_0.8 grid_3.3.3 nnet_7.3-12 data.table_1.10.0 survival_2.40-1
foreign_0.8-67 [25] latticeExtra_0.6-28 minqa_1.2.4
Formula_1.2-1 ggplot2_2.2.1 magrittr_1.5
Hmisc_4.0-2 scales_0.4.1 backports_1.0.5 [33] htmltools_0.3.5 MASS_7.3-45 splines_3.3.3
assertthat_0.1 colorspace_1.3-2 stringi_1.1.2
acepack_1.4.1 lazyeval_0.2.0 [41] munsell_0.4.3

출처

2017-03-14 21:18:40 user98678

R 3.3.2 : Mac OS X에서 lme4 + lmer 테스트 문제

답변

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