package dr.evomodel.clock;
import dr.evomodel.tree.TreeModel;
import dr.inference.model.Parameter;
import dr.math.MathUtils;
import dr.math.distributions.NormalDistribution;
/**
* Calculates the likelihood of a set of rate changes in a tree, assuming that rates are lognormally distributed
* cf Yang and Rannala 2006
*
* @author Michael Defoin Platel
*/
public class UCLikelihood extends RateEvolutionLikelihood {
public UCLikelihood(TreeModel tree, Parameter ratesParameter, Parameter variance, Parameter rootRate, boolean isLogSpace) {
super((isLogSpace) ? "LogNormally Distributed" : "Normally Distributed", tree, ratesParameter, rootRate, false);
this.isLogSpace = isLogSpace;
this.variance = variance;
addVariable(variance);
}
/**
* @return the log likelihood of the rate.
*/
double branchRateChangeLogLikelihood(double foo1, double rate, double foo2) {
double var = variance.getParameterValue(0);
double meanRate = rootRateParameter.getParameterValue(0);
if (isLogSpace) {
final double logmeanRate = Math.log(meanRate);
final double logRate = Math.log(rate);
return NormalDistribution.logPdf(logRate, logmeanRate - (var / 2.), Math.sqrt(var)) - logRate;
} else {
return NormalDistribution.logPdf(rate, meanRate, Math.sqrt(var));
}
}
double branchRateSample(double foo1, double foo2) {
double meanRate = rootRateParameter.getParameterValue(0);
double var = variance.getParameterValue(0);
if (isLogSpace) {
final double logMeanRate = Math.log(meanRate);
return Math.exp(MathUtils.nextGaussian() * Math.sqrt(var) + logMeanRate - (var / 2.));
} else {
return MathUtils.nextGaussian() * Math.sqrt(var) + meanRate;
}
}
private final Parameter variance;
boolean isLogSpace = false;
}