Marginal likelihood and posterior computation for complementary log-log ordinal BART model. More...

#include <leaf_model.h>

Public Member Functions
	CloglogOrdinalLeafModel (double a, double b)
	Construct a new CloglogOrdinalLeafModel object.

double	SplitLogMarginalLikelihood (CloglogOrdinalSuffStat &left_stat, CloglogOrdinalSuffStat &right_stat, double global_variance)
	Log marginal likelihood for a proposed split, evaluated only for observations that fall into the node being split.

double	NoSplitLogMarginalLikelihood (CloglogOrdinalSuffStat &suff_stat, double global_variance)
	Log marginal likelihood of a node, evaluated only for observations that fall into the node being split.

double	SuffStatLogMarginalLikelihood (CloglogOrdinalSuffStat &suff_stat, double global_variance)
	Helper function to compute log marginal likelihood from sufficient statistics.

double	PosteriorParameterShape (CloglogOrdinalSuffStat &suff_stat, double global_variance)
	Posterior shape parameter for leaf node log-gamma distribution.

double	PosteriorParameterRate (CloglogOrdinalSuffStat &suff_stat, double global_variance)
	Posterior rate parameter for leaf node log-gamma distribution.

void	SampleLeafParameters (ForestDataset &dataset, ForestTracker &tracker, ColumnVector &residual, Tree *tree, int tree_num, double global_variance, std::mt19937 &gen)
	Draw new parameters for every leaf node in `tree`, using a Gibbs update that conditions on the data, every other tree in the forest, and all model parameters. Samples from log-gamma: sample from gamma, then take log.

Detailed Description

Marginal likelihood and posterior computation for complementary log-log ordinal BART model.

Constructor & Destructor Documentation

StochTree::CloglogOrdinalLeafModel::CloglogOrdinalLeafModel	(	double	a,
		double	b
	)

inline

Construct a new CloglogOrdinalLeafModel object.

Parameters

a	shape parameter for log-gamma prior on leaf parameters
b	rate parameter for log-gamma prior on leaf parameters Log-gamma density: f(x) = b^a / Gamma(a) * exp(ax - bexp(x))

The documentation for this class was generated from the following file: