Uses of Class
edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood.Ret

Packages that use ConditionalGaussianLikelihood.Ret

Package	Description
edu.cmu.tetrad.search.score	This package contains classes for scoring causal graph models.

Uses of ConditionalGaussianLikelihood.Ret in edu.cmu.tetrad.search.score

Methods in edu.cmu.tetrad.search.score that return ConditionalGaussianLikelihood.Ret

Modifier and Type	Method	Description
ConditionalGaussianLikelihood.Ret	ConditionalGaussianLikelihood.getLikelihood(int i, int[] parents)	Returns the likelihood of variable i conditional on the given parents, assuming the continuous mixedVariables index by i or by the parents are jointly Gaussian conditional on the discrete comparison.
ConditionalGaussianLikelihood.Ret	ConditionalGaussianLikelihood.getLikelihood(int i, int[] parents, List<Integer> rows)	As ConditionalGaussianLikelihood.getLikelihood(int, int[]), but evaluated over exactly the given rows, passed explicitly so that concurrent callers (parallel FGES / BOSS scoring with testwise deletion) do not need to mutate shared state via ConditionalGaussianLikelihood.setRows(List).
ConditionalGaussianLikelihood.Ret	ConditionalGaussianLikelihood.getLikelihoodRatio(int i, int[] parents0, int[] parents1)	Returns the likelihood-ratio ingredients for the nested comparison of target i given parents0 (the smaller model) versus target i given parents1 (the larger model; parents0 should be a subset of parents1).
ConditionalGaussianLikelihood.Ret	ConditionalGaussianLikelihood.getLikelihoodRatio(int i, int[] parents0, int[] parents1, List<Integer> rows)	As ConditionalGaussianLikelihood.getLikelihoodRatio(int, int[], int[]), but evaluated over exactly the given rows, passed explicitly so that concurrent callers (the parallelized Markov checker, parallel constraint-based search) do not need to mutate shared state via ConditionalGaussianLikelihood.setRows(List).