BwUniCluster2.0/Software/R/Rjags: Difference between revisions
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<span style="color:red"><b>Note that the instructions provided below refer to R 4.2.1 (but not R 4.4.1)! We are currently updating our guides for R 4.4.1.</b></span> |
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= General information = |
= General information = |
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> install.packages("rjags", configure.args="--enable-rpath") |
> install.packages("rjags", configure.args="--enable-rpath") |
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> library(rjags) |
> library(rjags) |
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[[Category:BwUniCluster]] |
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[[Category:BwUniCluster_2.0]] |
Latest revision as of 18:13, 30 October 2024
Note that the instructions provided below refer to R 4.2.1 (but not R 4.4.1)! We are currently updating our guides for R 4.4.1.
General information
rjags is a R interface to use JAGS, Just another Gibbs Sampler. JAGS is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation
rjags needs a JAGS installation on the side. We recommend to compile via Intel compiler and with the Intel MKL library (Intel Math Kernel Library), which allows JAGS to use various efficient implementations of mathematical computations. These are, as of now, loaded alongside with the module R 4.1.2.
Installation
Please enter the following code, presented in the boxes below, directly into your shell/command line on bwUniCluster
#Load R module module load math/R/4.1.2 # Set up JAGS installation directory export JAGS_HOME=$HOME/sw/jags # Prepare JAGS source directory (if not yet existing) mkdir -p ~/src cd ~/src # Get JAGS source wget https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/Source/JAGS-4.3.1.tar.gz tar xf JAGS-4.3.1.tar.gz cd JAGS-4.3.1 rm JAGS-4.3.1.tar.gz # Install JAGS export CFLAGS="-O3 -axCORE-AVX512,CORE-AVX2,AVX -xSSE4.2 -fp-model strict -qopenmp" export CXXFLAGS="-O3 -std=c++14 -axCORE-AVX512,CORE-AVX2,AVX -xSSE4.2 -fp-model strict -qopenmp" ./configure --prefix=$JAGS_HOME --with-blas="-lmkl_rt -lpthread -lm" make make install cd # Set up environment export PKG_CONFIG_PATH=$JAGS_HOME/lib/pkgconfig export LD_RUN_PATH=$JAGS_HOME/lib # Install rjags package from within R session R -q > install.packages("rjags", configure.args="--enable-rpath") > library(rjags)