A friendly MCMC framework
Description
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC)
framework for implementing Metropolis-Hastings algorithm in a modular way
allowing users to specify automatic convergence checker, personalized
transition kernels, and out-of-the-box multiple MCMC chains using
parallel computing. Most of the methods implemented in this package can
be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods
included, we have: Haario (2001)
Adaptive Metropolis, Vihola (2012)
Robust Adaptive Metropolis, and Thawornwattana et
al. (2018) Mirror transition kernels.