Description: We focus here on Markov
Chain Monte Carlo (MCMC) methods, which attempt to simulate direct draws
from some complex distribution of interest. MCMC approaches are so-named because one uses the previous sample values to randomly generate the next sample
value, generating a Markov chain (as the transition probabilities between sample values are only a function of the most recent sample value).
To Search:
- [well_logging_process] - I read the time to write a master's degr
- [MCMC] - Peking University Professor Yu Jiangshen
- [MCMC] - This is on the MCM (Markov chain Monte C
- [mcsim] - MCSim is a general purpose modeling and
- [myfirst1] - Achieve Gibbs sampling, can be used to h
- [JAGS-2.2.0.tar] - Gibbs sampling algorithm based on source
File list (Check if you may need any files):
★mcmc-gibbs-intro.pdf
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