Package: StanHeaders 2.36.0.9000

StanHeaders: C++ Header Files for Stan

The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.

Authors:Ben Goodrich [cre, aut], Joshua Pritikin [ctb], Andrew Gelman [aut], Bob Carpenter [aut], Matt Hoffman [aut], Daniel Lee [aut], Michael Betancourt [aut], Marcus Brubaker [aut], Jiqiang Guo [aut], Peter Li [aut], Allen Riddell [aut], Marco Inacio [aut], Mitzi Morris [aut], Jeffrey Arnold [aut], Rob Goedman [aut], Brian Lau [aut], Rob Trangucci [aut], Jonah Gabry [aut], Alp Kucukelbir [aut], Robert Grant [aut], Dustin Tran [aut], Michael Malecki [aut], Yuanjun Gao [aut], Hamada S. Badr [aut], Trustees of Columbia University [cph], Lawrence Livermore National Security [cph], The Regents of the University of California [cph], Southern Methodist University [cph]