Man pages for Lucaweihs/sBIC
Computing the Singular BIC for Multiple Models

BinomialMixturesConstruct a poset of binomial mixture models.
emMainEM-algorithm for latent forests.
emStepsOne EM-iteration.
FactorAnalysesConstruct a poset of factor analysis models.
GaussianMixturesConstruct a poset of gaussian mixture models.
generateAllBinaryTreesGenerate all non-isomorphic binary trees.
getAllEdgesEdges representing the largest model.
getCovMatCreate a covariance matrix.
getDataReturn the set data.
getDimensionModel dimension.
getModelWithSupportGet model with the given support.
getNumFactorsForModelNumber of factors for a model.
getNumLeavesGet number of leaves.
getNumModelsNumber of models.
getNumSamplesNumber of samples in the set data.
getNumVerticesMaximum number of vertices.
getPhiGet the phi parameter.
getPriorThe prior on the models.
getSamplingCovMatSampling covariance matrix.
getSupportGet support for a given model.
getTopOrderTopological ordering of models.
LatentForestsConstruct a poset of gaussian latent forest models.
LCAsConstruct a poset of latent class analysis models.
learnCoefLearning coefficient
logLikeMultivariate gaussian log-likelihood.
logLikeMleMaximum likelihood for data.
logLikeMleHelperHelp compute the MLE.
MixtureModelsLinear collections of mixture models.
mleMaximum likelihood estimator.
parentsParents of a model.
ReducedRankRegressionsConstruct a poset of reduced rank regression models.
sBICCompute the sBIC.
sBIC-packagesBIC package documentation.
setDataSet data for a model poset.
setData.BinomialMixturesSet data for the binomial mixture models.
setData.FactorAnalysesSet data for the factor analysis models.
setData.GaussianMixturesSet data for the gaussian mixture models.
setData.LatentForestsSet data for the latent forest models.
setData.LCAsSet data for the LCA models.
setData.ReducedRankRegressionsSet data for the reduced rank regression models.
setPhiSet phi parameter.
Lucaweihs/sBIC documentation built on June 3, 2017, 3:34 a.m.