The exnexstan package provides a user-friendly interface to fitting EXNEX models in R without requiring the user to directly interface with a probabilistic programming language like BUGS, JAGS, or Stan.
Stan (https://mc-stan.org/) is used to fit the models using modern Hamiltonian Markov Chain Monte Carlo (HMC) sampling.
The exnexstan package is not on CRAN, but can be installed from GitHub using the install_github() function from the devtools package.
# Skip if devtools is already installed
install.packages("devtools")
devtools::install_github(repo = "https://github.com/maxdrohde/exnexstan")
To use exnexstan, the cmdstanr R package and the cmdstan software must be installed, working and up-to-date before exnexstan is installed.
cmdstanrcan be installed via GitHub (see https://mc-stan.org/cmdstanr/articles/cmdstanr.html).cmdstancan be installed from withincmdstanr(see https://mc-stan.org/cmdstanr/articles/cmdstanr.html#installing-cmdstan-1).
If you already have cmdstan installed, run
cmdstanr::install_cmdstan(overwrite=TRUE)
within R to make sure it is up-to-date. There can be errors when installing exnexstan if your cmdstan installation is outdated.
We provide two vignettes that demonstrate how to fit EXNEX models for binary data and count data with exnexstan.
- Binary data: https://maxdrohde.github.io/exnexstan/vignettes/exnex_binary_vignette.html
- Count data: https://maxdrohde.github.io/exnexstan/vignettes/exnex_poisson_vignette.html
For additional details on the functions, see the package documentation within R, or at the pkgdown site: https://maxdrohde.github.io/exnexstan/.
For the mathematical details of EXNEX and more in-depth examples, see the original paper by Neuenschwander et al. (2015).
To view the Stan code used to implement these models, you can view them here: https://github.com/maxdrohde/exnexstan/tree/master/inst.
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