R: Computing the Singular BIC for Multiple Models

# Computing the Singular BIC for Multiple Models

## Documentation for package ‘sBIC’ version 0.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

B E F G L M P R S

sBIC-package | sBIC package documentation.

## -- B --

BinomialMixtures | Construct a poset of binomial mixture models.

## -- E --

emMain | EM-algorithm for latent forests.
emMain.LatentForests | EM-algorithm for latent forests.
emSteps | One EM-iteration.
emSteps.LatentForests | One EM-iteration.

## -- F --

FactorAnalyses | Construct a poset of factor analysis models.

## -- G --

GaussianMixtures | Construct a poset of gaussian mixture models.
generateAllBinaryTrees | Generate all non-isomorphic binary trees.
getAllEdges | Edges representing the largest model.
getAllEdges.LatentForests | Edges representing the largest model.
getCovMat | Create a covariance matrix.
getCovMat.LatentForests | Create a covariance matrix.
getData | Return the set data.
getData.BinomialMixtures | Return the set data.
getData.FactorAnalyses | Return the set data.
getData.GaussianMixtures | Return the set data.
getData.LatentForests | Return the set data.
getData.LCAs | Return the set data.
getData.ReducedRankRegressions | Return the set data.
getDimension | Model dimension.
getDimension.BinomialMixtures | Model dimension.
getDimension.FactorAnalyses | Model dimension.
getDimension.GaussianMixtures | Model dimension.
getDimension.LatentForests | Model dimension.
getDimension.LCAs | Model dimension.
getDimension.ReducedRankRegressions | Model dimension.
getModelWithSupport | Get model with the given support.
getModelWithSupport.LatentForests | Get model with the given support.
getNumFactorsForModel | Number of factors for a model.
getNumFactorsForModel.FactorAnalyses | Number of factors for a model.
getNumLeaves | Get number of leaves.
getNumLeaves.LatentForests | Get number of leaves.
getNumModels | Number of models.
getNumModels.BinomialMixtures | Number of models.
getNumModels.FactorAnalyses | Number of models.
getNumModels.GaussianMixtures | Number of models.
getNumModels.LatentForests | Number of models.
getNumModels.LCAs | Number of models.
getNumModels.ReducedRankRegressions | Number of models.
getNumSamples | Number of samples in the set data.
getNumSamples.BinomialMixtures | Number of samples in the set data.
getNumSamples.FactorAnalyses | Number of samples in the set data.
getNumSamples.GaussianMixtures | Number of samples in the set data.
getNumSamples.LatentForests | Number of samples in the set data.
getNumSamples.LCAs | Number of samples in the set data.
getNumSamples.ReducedRankRegressions | Number of samples in the set data.
getNumVertices | Maximum number of vertices.
getNumVertices.LatentForests | Maximum number of vertices.
getPhi | Get the phi parameter.
getPhi.MixtureModels | Get the phi parameter.
getPrior | The prior on the models.
getPrior.BinomialMixtures | The prior on the models.
getPrior.FactorAnalyses | The prior on the models.
getPrior.GaussianMixtures | The prior on the models.
getPrior.LatentForests | The prior on the models.
getPrior.LCAs | The prior on the models.
getPrior.ReducedRankRegressions | The prior on the models.
getSamplingCovMat | Sampling covariance matrix.
getSamplingCovMat.LatentForests | Sampling covariance matrix.
getSupport | Get support for a given model.
getSupport.LatentForests | Get support for a given model.
getTopOrder | Topological ordering of models.
getTopOrder.BinomialMixtures | Topological ordering of models.
getTopOrder.FactorAnalyses | Topological ordering of models.
getTopOrder.GaussianMixtures | Topological ordering of models.
getTopOrder.LatentForests | Topological ordering of models.
getTopOrder.LCAs | Topological ordering of models.
getTopOrder.ReducedRankRegressions | Topological ordering of models.

## -- L --

LatentForests | Construct a poset of gaussian latent forest models.
LCAs | Construct a poset of latent class analysis models.
learnCoef | Learning coefficient
learnCoef.FactorAnalyses | Learning coefficient
learnCoef.LatentForests | Learning coefficient
learnCoef.MixtureModels | Learning coefficient
learnCoef.ReducedRankRegressions | Learning coefficient
logLike | Multivariate gaussian log-likelihood.
logLike.LatentForests | Multivariate gaussian log-likelihood.
logLikeMle | Maximum likelihood for data.
logLikeMle.BinomialMixtures | Maximum likelihood for data.
logLikeMle.FactorAnalyses | Maximum likelihood for data.
logLikeMle.GaussianMixtures | Maximum likelihood for data.
logLikeMle.LatentForests | Maximum likelihood for data.
logLikeMle.LCAs | Maximum likelihood for data.
logLikeMle.ReducedRankRegressions | Maximum likelihood for data.
logLikeMleHelper | Help compute the MLE.
logLikeMleHelper.ReducedRankRegressions | Help compute the MLE.

## -- M --

MixtureModels | Linear collections of mixture models.
mle | Maximum likelihood estimator.
mle.BinomialMixtures | Maximum likelihood estimator.
mle.FactorAnalyses | Maximum likelihood estimator.
mle.GaussianMixtures | Maximum likelihood estimator.
mle.LatentForests | Maximum likelihood estimator.
mle.LCAs | Maximum likelihood estimator.

## -- P --

parents | Parents of a model.
parents.FactorAnalyses | Parents of a model.
parents.LatentForests | Parents of a model.
parents.MixtureModels | Parents of a model.
parents.ReducedRankRegressions | Parents of a model.

## -- R --

ReducedRankRegressions | Construct a poset of reduced rank regression models.

## -- S --

sBIC | Compute the sBIC.
setData | Set data for a model poset.
setData.BinomialMixtures | Set data for the binomial mixture models.
setData.FactorAnalyses | Set data for the factor analysis models.
setData.GaussianMixtures | Set data for the gaussian mixture models.
setData.LatentForests | Set data for the latent forest models.
setData.LCAs | Set data for the LCA models.
setData.ReducedRankRegressions | Set data for the reduced rank regression models.
setPhi | Set phi parameter.
setPhi.MixtureModels | Set phi parameter.