文件名称：Probabilistic Inference Using MCMC
文件大小：1.08MB
文件格式：PDF
更新时间：2015-12-30 08:44:41
MCMC
Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods) are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibrium distribution. The state of the chain after a large number of steps is then used as a sample of the desired distribution. The quality of the sample improves as a function of the number of steps. -Wiki