Hi, I'm using the pRoloc package to train an TAGM-MCMC model on a proteome data set. For this a Markov Chain Monte Carlo simulation is used via the tagmMcmcTrain() function. However, if I try to run the simulation, an error message occurs:

 > tagm_params <- tagmMcmcTrain(data, fcol = "localization", numIter = 15000, burnin = 4000, thin = 10, numChains = 4)

error: chol(): decomposition failed
Fehler: BiocParallel errors
  element index: 1, 2, 3, 4
  first error: chol(): decomposition failed

I understand, that the problem roots in the covariance matrix not being positive definite. I confirmed this by calculating the eigenvalues of the covariance Matrix. I can correct this by calculating the nearest positive definite covariance matrix by using the nearPD() function. But how can I pass this corrected covariance matrix to the tagmMcmcTrain function?

Thank you very much in advance!

Could you provide the output of sessionInfo please. This was addressed end of last year, which should be available in the latest devel (version 1.23.1).

Yes sure, sorry I forgot that.

R version 3.5.1 (2018-07-02)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)

Matrix products: default

locale:
[1] LC_COLLATE=German_Germany.1252  LC_CTYPE=German_Germany.1252   
[3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C                   
[5] LC_TIME=German_Germany.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] pRoloc_1.22.1        BiocParallel_1.16.6  MLInterfaces_1.62.0 
 [4] cluster_2.0.7-1      annotate_1.60.1      XML_3.98-1.19       
 [7] AnnotationDbi_1.44.0 IRanges_2.16.0       MSnbase_2.8.3       
[10] ProtGenerics_1.14.0  S4Vectors_0.20.1     mzR_2.16.2          
[13] Rcpp_1.0.0           Biobase_2.42.0       BiocGenerics_0.28.0 

loaded via a namespace (and not attached):
  [1] snow_0.4-3            plyr_1.8.4            igraph_1.2.4         
  [4] lazyeval_0.2.1        splines_3.5.1         ggvis_0.4.4          
  [7] crosstalk_1.0.0       ggplot2_3.1.0         digest_0.6.18        
 [10] foreach_1.4.4         htmltools_0.3.6       viridis_0.5.1        
 [13] gdata_2.18.0          magrittr_1.5          memoise_1.1.0        
 [16] doParallel_1.0.14     mixtools_1.1.0        sfsmisc_1.1-3        
 [19] limma_3.38.3          recipes_0.1.4         gower_0.2.0          
 [22] rda_1.0.2-2.1         lpSolve_5.6.13        prettyunits_1.0.2    
 [25] colorspace_1.4-0      blob_1.1.1            xfun_0.5             
 [28] dplyr_0.8.0.1         crayon_1.3.4          RCurl_1.95-4.12      
 [31] hexbin_1.27.2         genefilter_1.64.0     impute_1.56.0        
 [34] survival_2.42-3       iterators_1.0.10      glue_1.3.0           
 [37] gtable_0.2.0          ipred_0.9-8           zlibbioc_1.28.0      
 [40] kernlab_0.9-27        prabclus_2.2-7        DEoptimR_1.0-8       
 [43] scales_1.0.0          vsn_3.50.0            mvtnorm_1.0-10       
 [46] DBI_1.0.0             viridisLite_0.3.0     xtable_1.8-3         
 [49] progress_1.2.0        bit_1.1-14            proxy_0.4-23         
 [52] mclust_5.4.2          preprocessCore_1.44.0 lava_1.6.5           
 [55] prodlim_2018.04.18    sampling_2.8          htmlwidgets_1.3      
 [58] httr_1.4.0            threejs_0.3.1         FNN_1.1.3            
 [61] RColorBrewer_1.1-2    fpc_2.1-11.1          modeltools_0.2-22    
 [64] pkgconfig_2.0.2       flexmix_2.3-15        nnet_7.3-12          
 [67] caret_6.0-81          tidyselect_0.2.5      rlang_0.3.1          
 [70] reshape2_1.4.3        later_0.8.0           munsell_0.5.0        
 [73] mlbench_2.1-1         tools_3.5.1           LaplacesDemon_16.1.1 
 [76] generics_0.0.2        RSQLite_2.1.1         pls_2.7-0            
 [79] stringr_1.4.0         mzID_1.20.1           ModelMetrics_1.2.2   
 [82] knitr_1.22            bit64_0.9-7           robustbase_0.93-3    
 [85] randomForest_4.6-14   purrr_0.3.1           dendextend_1.9.0     
 [88] ncdf4_1.16.1          nlme_3.1-137          whisker_0.3-2        
 [91] mime_0.6              biomaRt_2.38.0        compiler_3.5.1       
 [94] e1071_1.7-0.1         affyio_1.52.0         tibble_2.0.1         
 [97] stringi_1.3.1         lattice_0.20-35       trimcluster_0.1-2.1  
[100] Matrix_1.2-14         gbm_2.1.5             pillar_1.3.1         
[103] BiocManager_1.30.4    MALDIquant_1.18       data.table_1.12.0    
[106] bitops_1.0-6          httpuv_1.4.5.1        R6_2.4.0             
[109] pcaMethods_1.74.0     affy_1.60.0           hwriter_1.3.2        
[112] promises_1.0.1        gridExtra_2.3         codetools_0.2-15     
[115] MASS_7.3-50           gtools_3.8.1          assertthat_0.2.0     
[118] withr_2.1.2           diptest_0.75-7        hms_0.4.2            
[121] grid_3.5.1            rpart_4.1-13          timeDate_3043.102    
[124] coda_0.19-2           class_7.3-14          segmented_0.5-3.0    
[127] shiny_1.2.0           lubridate_1.7.4       base64enc_0.1-3