suggest.burn.log.likelihood: Suggest MCMC Burn-in from Log Likelihood

In Boom: Bayesian Object Oriented Modeling

Suggest MCMC Burn-in from Log Likelihood

Description

Suggests a burn-in period for an MCMC chain based on the log likelihood values simulated in the final few iterations of the chain.

Usage

  SuggestBurnLogLikelihood(log.likelihood, fraction = .10, quantile = .9)

Arguments

log.likelihood	A numeric vector giving the log likelihood values for each MCMC iteration.
fraction	The fraction of the chain that should be used to determine the log likelihood lower bound. The default setting looks in the final 25% of the MCMC run. Must be an number less than 1. If fraction <= 0 then a 0 burn-in is returned.
quantile	The quantile of the values in the final fraction that must be exceeded before the burn-in period is declared over.

Details

Looks at the last fraction of the log.likelihood sequence and finds a specified quantile to use as a threshold. Returns the first iteration where log.likelihood exceeds this threshold.

Value

Returns a suggested number of iterations to discard. This can be 0 if fraction == 0, which is viewed as a signal that no burn-in is desired.

Author(s)

Steven L. Scott [e-mail]

Boom documentation built on Nov. 10, 2022, 5:56 p.m.