[R-sig-ME] Error using MCMCglmm
Kamal Atmeh
k@m@|@@tmeh @end|ng |rom hotm@||@com
Mon Dec 27 20:05:51 CET 2021
Hi Jarrod,
Thank you for your answer.
Yes I transformed the dataset to a classic dataframe but the error remained.
If it can help, please find below my sessionInfo(). I eventually loaded
the tidyverse.
Cheers,
Kamal
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19043)
Matrix products: default
locale:
[1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252
[3] LC_MONETARY=French_France.1252 LC_NUMERIC=C
[5] LC_TIME=French_France.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] MCMCglmm_2.29 ape_5.4-1 coda_0.19-4 performance_0.7.0
[5] MuMIn_1.43.17 visreg_2.7.0 merTools_0.5.2 arm_1.11-2
[9] MASS_7.3-53 glmmTMB_1.1.2.3 lmerTest_3.1-3 lme4_1.1-27.1
[13] Matrix_1.4-0 scales_1.1.1 forcats_0.5.1 stringr_1.4.0
[17] dplyr_1.0.7 purrr_0.3.4 readr_1.4.0 tidyr_1.1.3
[21] tibble_3.0.4 ggplot2_3.3.5 tidyverse_1.3.1 plyr_1.8.6
loaded via a namespace (and not attached):
[1] cubature_2.0.4.2 TH.data_1.0-10 minqa_1.2.4 colorspace_1.4-1
[5] ellipsis_0.3.2 estimability_1.3 htmlTable_2.2.1
corpcor_1.6.9
[9] base64enc_0.1-3 fs_1.5.0 rstudioapi_0.13 fansi_0.4.1
[13] mvtnorm_1.1-1 lubridate_1.7.10 xml2_1.3.2 codetools_0.2-16
[17] splines_4.0.3 knitr_1.33 Formula_1.2-4 jsonlite_1.7.2
[21] nloptr_1.2.2.2 packrat_0.6.0 broom_0.7.8 cluster_2.1.0
[25] dbplyr_2.1.1 png_0.1-7 broom.mixed_0.2.6
shiny_1.5.0
[29] compiler_4.0.3 httr_1.4.2 emmeans_1.6.1
backports_1.2.1
[33] fastmap_1.1.0 assertthat_0.2.1 cli_2.5.0 later_1.2.0
[37] htmltools_0.5.1.1 tools_4.0.3 gtable_0.3.0 glue_1.4.2
[41] reshape2_1.4.4 Rcpp_1.0.7 cellranger_1.1.0 vctrs_0.3.8
[45] nlme_3.1-149 iterators_1.0.13 insight_0.14.2
tensorA_0.36.1
[49] xfun_0.24 rvest_1.0.0 mime_0.9 lifecycle_1.0.0
[53] zoo_1.8-8 promises_1.1.1 hms_1.1.0 parallel_4.0.3
[57] sandwich_3.0-0 TMB_1.7.22 RColorBrewer_1.1-2
gridExtra_2.3
[61] rpart_4.1-15 latticeExtra_0.6-29 stringi_1.5.3
bayestestR_0.10.0
[65] foreach_1.5.1 blme_1.0-5 checkmate_2.0.0 boot_1.3-25
[69] rlang_0.4.11 pkgconfig_2.0.3 lattice_0.20-41
htmlwidgets_1.5.3
[73] tidyselect_1.1.0 magrittr_2.0.1 R6_2.4.1 generics_0.1.0
[77] Hmisc_4.5-0 multcomp_1.4-14 DBI_1.1.1 pillar_1.6.4
[81] haven_2.4.1 foreign_0.8-80 withr_2.3.0 survival_3.2-7
[85] abind_1.4-5 nnet_7.3-14 modelr_0.1.8 crayon_1.4.1
[89] utf8_1.1.4 jpeg_0.1-8.1 grid_4.0.3 readxl_1.3.1
[93] data.table_1.14.0 reprex_2.0.0 digest_0.6.27 xtable_1.8-4
[97] httpuv_1.6.1 numDeriv_2016.8-1.1 stats4_4.0.3 munsell_0.5.0
Le 27/12/2021 à 19:49, Jarrod Hadfield a écrit :
> Hi,
>
> Is your data frame a tibble? If so, make it a standard data frame and
> retry.
>
> Cheers,
>
> Jarrod
>
> On 27/12/2021 18:46, Kamal Atmeh wrote:
>> This email was sent to you by someone outside the University.
>> You should only click on links or attachments if you are certain that
>> the email is genuine and the content is safe.
>>
>> Dear list,
>>
>> I am trying to run bayesian phylogenetic mixed models using MCMCglmm but
>> I keep getting the following error:
>>
>> " Error in MCMCglmm(ltau ~ x * x2 + lbmM + age + lmean_ndvi + :
>> no slot of name "i" for this object of class "ddiMatrix" "
>>
>> This is not the first time I use MCMCglmm and it usually works
>> flawlessly. I thought that there may be a conflict with the "tidyverse"
>> package since some functions of "Matrix" are masked, but I tried to run
>> the model without loading the "tidyverse" package and still received the
>> same error. I was not able to find answers online and am thus turning to
>> this list for answers if you can help please.
>>
>> I am running the following model:
>>
>> >>> prior1 <-list (G = list(G1 = list(V = 1, nu = 0.02)
>> ,G2 = list(V = 1, nu = 0.02)
>> ,G3 = list(V = 1, nu = 0.02)
>> ,G4 = list(V = 1, nu = 0.02)),
>> R = list(V = 1, nu = 0.02)
>> )
>>
>> >>> mod_tau_mc <- MCMCglmm(ltau ~ x * x2+ # x and x2 are categorical
>> variables
>> lbmM + # continuous variable
>> age + # categorical
>> lmean_ndvi + # continuous
>> lrange_ndvi + # continuous
>> lnb.loc + # continuous
>> lduration # continuous
>> , random =
>> ~sp_phylo+species2+phylo_pop+phylo_pop_id
>> , ginverse = list(sp_phylo = inv.phylo$Ainv)
>> # include a custom matrix for argument sp_phylo
>> , family = "gaussian"
>> , prior = prior1
>> , data = dt
>> , nitt = 22e+03 # number of iteration
>> after burnin
>> , burnin = 2000 # number of iteration
>> before beginning sample
>> , thin = 100 # nb of iteration between
>> sample
>> , pr = TRUE) #save random posterior
>> distribution
>>
>> I would greatly appreciate your help and happy to provide further
>> information if needed!
>>
>> Thank you in advance!
>>
>> Kamal
>>
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