Nothing
### Gibbs sampler and M-H for step 2, mainly for hyperparameters.
### Draw prior for log mixture normal distribtuion.
my.pPropTypeNoObs.logmixture <- function(n.G, phi.Curr,
p.Curr, hp.param){
### Dispatch.
paramlog.Curr <- p.Curr
log.phi.Curr <- log(phi.Curr)
### Propose new mixture parameters.
proplist <- my.propose.paramlog(paramlog.Curr, log.phi.Curr, hp.param)
### Update prior's acceptance and adaptive.
my.update.acceptance("p", 1)
my.update.adaptive("p", 1)
### Only nu.Phi and sigma.Phi are used.
ret <- proplist$paramlog
ret
} # my.pPropTypeNoObs.logmixture().
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.