Authors@R: c(person("Stan Development Team", role=c('aut','cph')), person(c("Joshua","N."), "Pritikin", email="jpritikin@pobox.com", role=c('cre','com')))
Description: The C++ header files associated with the Stan project. Stan is a probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling and penalized maximum likelihood estimation with optimization. See <http://mc-stan.org/> for more information.
Author: Stan Development Team [aut, cph],

Description: The C++ header files of the Stan project are provided by this package, but it contains no R code, shared objects, vignettes, or function documentation. It is only 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 Bayesian statistical inference via Markov Chain Monte Carlo and (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.

Description: The C++ header files of the Stan project are provided by this package, but it contains no R code, shared objects, vignettes, or function documentation. It is only 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 Bayesian statistical inference via Markov Chain Monte Carlo and (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.