calculates the Maxiumum APosteriori value (MAP)
MAP(bayesianOutput, ...)
| bayesianOutput | an object of class BayesianOutput (mcmcSampler, smcSampler, or mcmcList) |
|---|---|
| ... | optional values to be passed on the the getSample function |
Currently, this function simply returns the parameter combination with the highest posterior in the chain. A more refined option would be to take the MCMC sample and do additional calculations, e.g. use an optimizer, a kerne delnsity estimator, or some other tool to search / interpolate around the best value in the chain