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These instructions were for an older Teton cluster, in principle the process should work for Beartooth and other clusters - but with updated module loads. |
Overview
RStan: The R interface to Stan. It is distributed on CRAN as the RStan package and its source code is hosted on GitHub.
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Note: This example used rstan Version: 2.21.2, and was built using R 4.0.2 (built using the gcc compiler).
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[]$ module load gcc/7.3.0 r/4.0.2-py27
[]$ R
R version 4.0.2 (2020-06-22) -- "Taking Off Again"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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> Sys.setenv(DOWNLOAD_STATIC_LIBV8=1)
> install.packages(c("V8", "rstan"), dependencies=TRUE)
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NOTE: rstan has LOTS of dependencies and depending what you already do/don't have installed this could take an hour.
‘colorspace’, ‘utf8’, ‘ps’, ‘nlme’, ‘farver’, ‘labeling’, ‘lifecycle’, ‘munsell’, ‘RColorBrewer’,
‘viridisLite’, ‘ellipsis’, ‘fansi’, ‘magrittr’, ‘pillar’, ‘pkgconfig’, ‘vctrs’, ‘backports’,
‘processx’, ‘assertthat’, ‘lattice’, ‘digest’, ‘glue’, ‘gtable’, ‘isoband’, ‘MASS’, ‘mgcv’,
‘rlang’, ‘scales’, ‘tibble’, ‘checkmate’, ‘matrixStats’, ‘callr’, ‘cli’, ‘crayon’, ‘desc’,
‘prettyunits’, ‘R6’, ‘rprojroot’, ‘Matrix’, ‘StanHeaders’, ‘ggplot2’, ‘inline’, ‘gridExtra’,
‘RcppParallel’, ‘loo’, ‘pkgbuild’, ‘withr’, ‘RcppEigen’, ‘BH’
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> library(rstan)
Loading required package: StanHeaders
Loading required package: ggplot2
code for methods in class “Rcpp_model_base” was not checked for suspicious field assignments (recommended package ‘codetools’ not available?)
code for methods in class “Rcpp_model_base” was not checked for suspicious field assignments (recommended package ‘codetools’ not available?)
code for methods in class “Rcpp_stan_fit” was not checked for suspicious field assignments (recommended package ‘codetools’ not available?)
code for methods in class “Rcpp_stan_fit” was not checked for suspicious field assignments (recommended package ‘codetools’ not available?)
rstan (Version 2.21.2, GitRev: 2e1f913d3ca3)
For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores()).
To avoid recompilation of unchanged Stan programs, we recommend calling
rstan_options(auto_write = TRUE) |
Installing rstan version before V8 dependency
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