public final String getPerformanceSuggestion() {
double prob = MCMCOperator.Utils.getAcceptanceProbability(this);
double targetProb = getTargetAcceptanceProbability();
double sf = OperatorUtils.optimizeScaleFactor(scaleFactor, prob, targetProb);
dr.util.NumberFormatter formatter = new dr.util.NumberFormatter(5);
if (prob < getMinimumGoodAcceptanceLevel()) {
return "Try setting scaleFactor to about " + formatter.format(sf);
} else if (prob > getMaximumGoodAcceptanceLevel()) {
return "Try setting scaleFactor to about " + formatter.format(sf);
} else return "";
}
/**
* Updates the proposal parameter, based on the target acceptance probability This method relies
* on the proposal parameter being a decreasing function of acceptance probability.
*
* @param op The operator
* @param logr
*/
private void coerceAcceptanceProbability(CoercableMCMCOperator op, double logr) {
if (isCoercable(op)) {
final double p = op.getCoercableParameter();
final double i = schedule.getOptimizationTransform(MCMCOperator.Utils.getOperationCount(op));
final double target = op.getTargetAcceptanceProbability();
final double newp = p + ((1.0 / (i + 1.0)) * (Math.exp(logr) - target));
if (newp > -Double.MAX_VALUE && newp < Double.MAX_VALUE) {
op.setCoercableParameter(newp);
}
}
}
