Leiyue Li

Leiyue Li

Assistant Professor of Data Science

How to get “RStan” to work in Rstudio

less than 1 minute read

Published:

I came across two error messages while using the $\bf{rstan}$ package in Rstudio. The error messages read as follows:

  • Error 1: “failed to create lock directory “
  • Error 2: “compileCode(f, code, language = language, verbose = verbose)”

$\textbf{Operating system:}$ Windows, $\textbf{R version:}$ 4.2.3.

Solutions:

  • Error 1 was easy to fix, simply run the following line before installing the package.
options("install.lock"=FALSE)
  • Error 2 was a bit tricky. I tried with several solutions and none of it worked. I then learned from this link that the current version of RStan on CRAN is not compatible with R 4.2.3. The following lines will resolve the error.
remove.packages(c("StanHeaders","rstan"))
install.packages("StanHeaders", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
install.packages("rstan", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
library(rstan)

Now you can check by running the example model code from Stan, and you should be able to run the following line without encountering any error messages.

example(stan_model, package = "rstan", run.dontrun = TRUE)

You May Also Enjoy

Learning R with swirl

1 minute read

Published:

Recently, I enrolled in an online course and stumbled upon swirl, a package for learning R, in R. I think that this is a great tool and an excellent way for beginners to learn R. I quickly fall in love with it. I believe there’s something for everyone on swirl, whether you’re a complete beginner or an experienced R user looking to expand skills. Thus, in this blog post, I’d like to share some of the courses in swirl that I found helpful. More information about swirl can be found in this link.

Continuous Updates: R Tricks I Found Useful

2 minute read

Published:

Welcome to this continuously updated blog post where I’ll be sharing R tips and tricks that I find helpful while coding. These range from simple one-liners to more complex functions that can save you time and effort. Some of the examples below may be too specific and not useful to you, while others are general R tips. I’m always interested in finding efficient solutions to complex problems and simplifying my code.