r-cran-rstan - 2.32.5-2 main

User-facing R functions are provided to parse, compile, test, estimate,
and analyze Stan models by accessing the header-only Stan library
provided by the 'StanHeaders' package. The Stan project develops a
probabilistic programming language that implements full Bayesian
statistical inference via Markov Chain Monte Carlo, rough Bayesian
inference via 'variational' approximation, and (optionally penalized)
maximum likelihood estimation via optimization. In all three cases,
automatic differentiation is used to quickly and accurately evaluate
gradients without burdening the user with the need to derive the partial
derivatives.