Basic R programming.- Random variable generation.- Monte Carlo integration.- Controling and accelerating convergence.- Monte Carlo Optimization.- Metropolis-Hastings algorithms.- Gibbs samplers.- Convergence Monitoring for MCMC algorithms.
Basic R Programming.- Random Variable Generation.- Monte Carlo Integration.- Controlling and Accelerating Convergence.- Monte Carlo Optimization.- Metropolis#x2013;Hastings Algorithms.- Gibbs Samplers.- Convergence Monitoring and Adaptation for MCMC Algorithms.
The first book to present modern Monte Carlo and Markov Chain Monte Carlo (MCMC) methods from a practical perspective through a guided implementation in the R language
All concepts are carefully described with the abstract theoretical background replaced with a corresponding R program that the reader can use and modify at will
The whole entire series of examples from the book is accompanied by a free R package called mcsm that allows for immediate experimentation