Hi, thank you for your bug report! > You find a related error if you try install.packages("isoband"), which could work as a test case: > > /gnu/store/741057r2x06zwg6zcmqmdyv51spm6n9i-gfortran-7.5.0-lib/lib/libstdc++.so.6: version > `GLIBCXX_3.4.26' not found (required by > /home/kept/Dotfiles/R/x86_64-unknown-linux-gnu-library/4.1/00LOCK-isoband/00new/isoband/libs/isoband.so) “install.packages” will only work if you carefully control your environment. It will not do the right thing when you use it on a foreign distro, for example, because it would likely pick the system’s compiler toolchain to build things that are eventually incompatible with the libraries used by R from Guix. Here’s an old blog post that explains the problem and how to work around it if you must use “install.packages”: https://elephly.net/posts/2017-03-24-r-with-guix.html I haven’t been able to reproduce your problem, though. Here’s what I did: --8<---------------cut here---------------start------------->8--- $ guix shell -C r-minimal r-rstan -D r-minimal -- R R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid" Copyright (C) 2022 The R Foundation for Statistical Computing Platform: x86_64-unknown-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > 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 2.21.5, 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) > scode <- " parameters { real y[2]; } model { y[1] ~ normal(0, 1); y[2] ~ double_exponential(0, 2); } " fit1 <- stan(model_code = scode, iter = 10, verbose = FALSE) + + + + + + + + > fit1 code for methods in class "Rcpp_stan_fit4model139796fca_b524cd829fcb9f50f6761f2451b62eec" was not checked for suspicious field assignments (recommended package 'codetools' not available?) code for methods in class "Rcpp_stan_fit4model139796fca_b524cd829fcb9f50f6761f2451b62eec" was not checked for suspicious field assignments (recommended package 'codetools' not available?) SAMPLING FOR MODEL 'b524cd829fcb9f50f6761f2451b62eec' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 6e-06 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.06 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: WARNING: No variance estimation is Chain 1: performed for num_warmup < 20 Chain 1: Chain 1: Iteration: 1 / 10 [ 10%] (Warmup) Chain 1: Iteration: 2 / 10 [ 20%] (Warmup) Chain 1: Iteration: 3 / 10 [ 30%] (Warmup) Chain 1: Iteration: 4 / 10 [ 40%] (Warmup) Chain 1: Iteration: 5 / 10 [ 50%] (Warmup) Chain 1: Iteration: 6 / 10 [ 60%] (Sampling) Chain 1: Iteration: 7 / 10 [ 70%] (Sampling) Chain 1: Iteration: 8 / 10 [ 80%] (Sampling) Chain 1: Iteration: 9 / 10 [ 90%] (Sampling) Chain 1: Iteration: 10 / 10 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0.000157 seconds (Warm-up) Chain 1: 0.000123 seconds (Sampling) Chain 1: 0.00028 seconds (Total) Chain 1: SAMPLING FOR MODEL 'b524cd829fcb9f50f6761f2451b62eec' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 3e-06 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.03 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: WARNING: No variance estimation is Chain 2: performed for num_warmup < 20 Chain 2: Chain 2: Iteration: 1 / 10 [ 10%] (Warmup) Chain 2: Iteration: 2 / 10 [ 20%] (Warmup) Chain 2: Iteration: 3 / 10 [ 30%] (Warmup) Chain 2: Iteration: 4 / 10 [ 40%] (Warmup) Chain 2: Iteration: 5 / 10 [ 50%] (Warmup) Chain 2: Iteration: 6 / 10 [ 60%] (Sampling) Chain 2: Iteration: 7 / 10 [ 70%] (Sampling) Chain 2: Iteration: 8 / 10 [ 80%] (Sampling) Chain 2: Iteration: 9 / 10 [ 90%] (Sampling) Chain 2: Iteration: 10 / 10 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 0.000146 seconds (Warm-up) Chain 2: 0.000132 seconds (Sampling) Chain 2: 0.000278 seconds (Total) Chain 2: SAMPLING FOR MODEL 'b524cd829fcb9f50f6761f2451b62eec' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 6e-06 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.06 seconds. Chain 3: Adjust your expectations accordingly! Chain 3: Chain 3: Chain 3: WARNING: No variance estimation is Chain 3: performed for num_warmup < 20 Chain 3: Chain 3: Iteration: 1 / 10 [ 10%] (Warmup) Chain 3: Iteration: 2 / 10 [ 20%] (Warmup) Chain 3: Iteration: 3 / 10 [ 30%] (Warmup) Chain 3: Iteration: 4 / 10 [ 40%] (Warmup) Chain 3: Iteration: 5 / 10 [ 50%] (Warmup) Chain 3: Iteration: 6 / 10 [ 60%] (Sampling) Chain 3: Iteration: 7 / 10 [ 70%] (Sampling) Chain 3: Iteration: 8 / 10 [ 80%] (Sampling) Chain 3: Iteration: 9 / 10 [ 90%] (Sampling) Chain 3: Iteration: 10 / 10 [100%] (Sampling) Chain 3: Chain 3: Elapsed Time: 0.000271 seconds (Warm-up) Chain 3: 0.000253 seconds (Sampling) Chain 3: 0.000524 seconds (Total) Chain 3: SAMPLING FOR MODEL 'b524cd829fcb9f50f6761f2451b62eec' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 5e-06 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.05 seconds. Chain 4: Adjust your expectations accordingly! Chain 4: Chain 4: Chain 4: WARNING: No variance estimation is Chain 4: performed for num_warmup < 20 Chain 4: Chain 4: Iteration: 1 / 10 [ 10%] (Warmup) Chain 4: Iteration: 2 / 10 [ 20%] (Warmup) Chain 4: Iteration: 3 / 10 [ 30%] (Warmup) Chain 4: Iteration: 4 / 10 [ 40%] (Warmup) Chain 4: Iteration: 5 / 10 [ 50%] (Warmup) Chain 4: Iteration: 6 / 10 [ 60%] (Sampling) Chain 4: Iteration: 7 / 10 [ 70%] (Sampling) Chain 4: Iteration: 8 / 10 [ 80%] (Sampling) Chain 4: Iteration: 9 / 10 [ 90%] (Sampling) Chain 4: Iteration: 10 / 10 [100%] (Sampling) Chain 4: Chain 4: Elapsed Time: 0.00014 seconds (Warm-up) Chain 4: 0.000132 seconds (Sampling) Chain 4: 0.000272 seconds (Total) Chain 4: Warning message: The largest R-hat is 1.07, indicating chains have not mixed. Running the chains for more iterations may help. See https://mc-stan.org/misc/warnings.html#r-hat > > Inference for Stan model: b524cd829fcb9f50f6761f2451b62eec. 4 chains, each with iter=10; warmup=5; thin=1; post-warmup draws per chain=5, total post-warmup draws=20. mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat y[1] -0.02 0.20 1.02 -1.80 -0.68 -0.05 0.59 1.86 26 0.89 y[2] 2.06 0.49 1.81 -1.29 0.78 1.96 3.48 5.00 14 1.08 lp__ -1.65 0.17 0.85 -3.08 -2.20 -1.64 -1.01 -0.41 26 0.81 Samples were drawn using NUTS(diag_e) at Tue Jul 12 17:28:00 2022. For each parameter, n_eff is a crude measure of effective sample size, and Rhat is the potential scale reduction factor on split chains (at convergence, Rhat=1). > --8<---------------cut here---------------end--------------->8--- Could you please show us an example like the above that fails when run in “guix shell -C”? Please also provide the output of “guix describe -f channels”. Thank you! -- Ricardo