MAP {BayesianTools}

calculates the Maxiumum APosteriori value (MAP)

Description

calculates the Maxiumum APosteriori value (MAP)

Usage

MAP(bayesianOutput, ...)

Arguments

bayesianOutput

an object of class BayesianOutput (mcmcSampler, smcSampler, or mcmcList)

...

optional values to be passed on the the getSample function

Details

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

Author(s)

Florian Hartig

See Also

WAIC, DIC, marginalLikelihood