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; }