Bibliography
This package is hidden from search results because it is not hosted in the universe of the upstream owner
cranhaven. To fix this you can add URL: https://cranhaven.r-universe.dev/sBIC to the package DESCRIPTION file. See also theR-universe documentation.Package: sBIC 0.2.0
Luca Weihs
sBIC: Computing the Singular BIC for Multiple Models
Computes the sBIC for various singular model collections including: binomial mixtures, factor analysis models, Gaussian mixtures, latent forests, latent class analyses, and reduced rank regressions.
Authors:
sBIC_0.2.0.tar.gz
sBIC_0.2.0.zip(r-4.7-x86_64)sBIC_0.2.0.zip(r-4.7-arm64)sBIC_0.2.0.zip(r-4.6-x86_64)sBIC_0.2.0.zip(r-4.6-arm64)sBIC_0.2.0.zip(r-4.5-x86_64)
sBIC_0.2.0.tgz(r-4.6-x86_64)sBIC_0.2.0.tgz(r-4.6-arm64)sBIC_0.2.0.tgz(r-4.5-x86_64)sBIC_0.2.0.tgz(r-4.5-arm64)
sBIC_0.2.0.tar.gz(r-4.7-arm64)sBIC_0.2.0.tar.gz(r-4.7-x86_64)sBIC_0.2.0.tar.gz(r-4.6-arm64)sBIC_0.2.0.tar.gz(r-4.6-x86_64)
sBIC_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sBIC/json (API)
| # Install 'sBIC' in R: |
| install.packages('sBIC', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lucaweihs/sbic/issues
Last updated from:5f0369fe72 (on package/sBIC). Checks:13 WARNING, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | WARNING | 99 | ||
| linux-devel-x86_64 | WARNING | 132 | ||
| source / vignettes | OK | 198 | ||
| linux-release-arm64 | WARNING | 106 | ||
| linux-release-x86_64 | WARNING | 137 | ||
| macos-release-arm64 | WARNING | 115 | ||
| macos-release-x86_64 | WARNING | 233 | ||
| macos-oldrel-arm64 | WARNING | 107 | ||
| macos-oldrel-x86_64 | WARNING | 235 | ||
| windows-devel-arm64 | WARNING | 206 | ||
| windows-devel-x86_64 | WARNING | 130 | ||
| windows-release-arm64 | WARNING | 199 | ||
| windows-release-x86_64 | WARNING | 90 | ||
| windows-oldrel-x86_64 | WARNING | 93 | ||
| wasm-release | OK | 105 |
Exports:BinomialMixturesemMainemMain.LatentForestsemStepsemSteps.LatentForestsFactorAnalysesGaussianMixturesgenerateAllBinaryTreesgetAllEdgesgetAllEdges.LatentForestsgetCovMatgetCovMat.LatentForestsgetDatagetData.BinomialMixturesgetData.FactorAnalysesgetData.GaussianMixturesgetData.LatentForestsgetData.LCAsgetData.ReducedRankRegressionsgetDimensiongetDimension.BinomialMixturesgetDimension.FactorAnalysesgetDimension.GaussianMixturesgetDimension.LatentForestsgetDimension.LCAsgetDimension.ReducedRankRegressionsgetModelWithSupportgetModelWithSupport.LatentForestsgetNumFactorsForModelgetNumFactorsForModel.FactorAnalysesgetNumLeavesgetNumLeaves.LatentForestsgetNumModelsgetNumModels.BinomialMixturesgetNumModels.FactorAnalysesgetNumModels.GaussianMixturesgetNumModels.LatentForestsgetNumModels.LCAsgetNumModels.ReducedRankRegressionsgetNumSamplesgetNumSamples.BinomialMixturesgetNumSamples.FactorAnalysesgetNumSamples.GaussianMixturesgetNumSamples.LatentForestsgetNumSamples.LCAsgetNumSamples.ReducedRankRegressionsgetNumVerticesgetNumVertices.LatentForestsgetPhigetPhi.MixtureModelsgetPriorgetPrior.BinomialMixturesgetPrior.FactorAnalysesgetPrior.GaussianMixturesgetPrior.LatentForestsgetPrior.LCAsgetPrior.ReducedRankRegressionsgetSamplingCovMatgetSamplingCovMat.LatentForestsgetSupportgetSupport.LatentForestsgetTopOrdergetTopOrder.BinomialMixturesgetTopOrder.FactorAnalysesgetTopOrder.GaussianMixturesgetTopOrder.LatentForestsgetTopOrder.LCAsgetTopOrder.ReducedRankRegressionsLatentForestsLCAslearnCoeflearnCoef.FactorAnalyseslearnCoef.LatentForestslearnCoef.MixtureModelslearnCoef.ReducedRankRegressionslogLikelogLike.LatentForestslogLikeMlelogLikeMle.BinomialMixtureslogLikeMle.FactorAnalyseslogLikeMle.GaussianMixtureslogLikeMle.LatentForestslogLikeMle.LCAslogLikeMle.ReducedRankRegressionslogLikeMleHelperlogLikeMleHelper.ReducedRankRegressionsMixtureModelsmlemle.BinomialMixturesmle.FactorAnalysesmle.GaussianMixturesmle.LatentForestsmle.LCAsparentsparents.FactorAnalysesparents.LatentForestsparents.MixtureModelsparents.ReducedRankRegressionsReducedRankRegressionssBICsetDatasetData.BinomialMixturessetData.FactorAnalysessetData.GaussianMixturessetData.LatentForestssetData.LCAssetData.ReducedRankRegressionssetPhisetPhi.MixtureModels
Dependencies:clicombinatcpp11flexmixgluehashigraphlatticelifecyclemagrittrMASSMatrixmclustmodeltoolsnnetpkgconfigpoLCAR.methodsS3R.ooRcpprlangscatterplot3dvctrs
Binomial Mixtures
Last update: 2026-10-12
Started: 2026-10-12
Factor Analysis
Last update: 2026-10-12
Started: 2026-10-12
Gaussian Mixtures
Bibliography
Last update: 2026-10-12
Started: 2026-10-12
Introduction to sBIC
Purpose | Object oriented approach | Example | References
Last update: 2026-10-12
Started: 2026-10-12
Latent Class Analysis
Simulation | Fitting an LCA model | Singular BIC for LCA | A simulation study | Bibliography
Last update: 2026-10-12
Started: 2026-10-12
Reduced Rank Regression
Simulating reduced rank regression data | Singular BIC for rank selection | Simulation study of rank selection | Bibliography
Last update: 2026-10-12
Started: 2026-10-12
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| sBIC package documentation. | sBIC-package |
| Construct a poset of binomial mixture models. | BinomialMixtures |
| EM-algorithm for latent forests. | emMain emMain.LatentForests |
| One EM-iteration. | emSteps emSteps.LatentForests |
| Construct a poset of factor analysis models. | FactorAnalyses |
| Construct a poset of gaussian mixture models. | GaussianMixtures |
| Generate all non-isomorphic binary trees. | generateAllBinaryTrees |
| Edges representing the largest model. | getAllEdges getAllEdges.LatentForests |
| Create a covariance matrix. | getCovMat getCovMat.LatentForests |
| Return the set data. | getData getData.BinomialMixtures getData.FactorAnalyses getData.GaussianMixtures getData.LatentForests getData.LCAs getData.ReducedRankRegressions |
| Model dimension. | getDimension getDimension.BinomialMixtures getDimension.FactorAnalyses getDimension.GaussianMixtures getDimension.LatentForests getDimension.LCAs getDimension.ReducedRankRegressions |
| Get model with the given support. | getModelWithSupport getModelWithSupport.LatentForests |
| Number of factors for a model. | getNumFactorsForModel getNumFactorsForModel.FactorAnalyses |
| Get number of leaves. | getNumLeaves getNumLeaves.LatentForests |
| Number of models. | getNumModels getNumModels.BinomialMixtures getNumModels.FactorAnalyses getNumModels.GaussianMixtures getNumModels.LatentForests getNumModels.LCAs getNumModels.ReducedRankRegressions |
| Number of samples in the set data. | getNumSamples getNumSamples.BinomialMixtures getNumSamples.FactorAnalyses getNumSamples.GaussianMixtures getNumSamples.LatentForests getNumSamples.LCAs getNumSamples.ReducedRankRegressions |
| Maximum number of vertices. | getNumVertices getNumVertices.LatentForests |
| Get the phi parameter. | getPhi getPhi.MixtureModels |
| The prior on the models. | getPrior getPrior.BinomialMixtures getPrior.FactorAnalyses getPrior.GaussianMixtures getPrior.LatentForests getPrior.LCAs getPrior.ReducedRankRegressions |
| Sampling covariance matrix. | getSamplingCovMat getSamplingCovMat.LatentForests |
| Get support for a given model. | getSupport getSupport.LatentForests |
| Topological ordering of models. | getTopOrder getTopOrder.BinomialMixtures getTopOrder.FactorAnalyses getTopOrder.GaussianMixtures getTopOrder.LatentForests getTopOrder.LCAs getTopOrder.ReducedRankRegressions |
| Construct a poset of gaussian latent forest models. | LatentForests |
| Construct a poset of latent class analysis models. | LCAs |
| Learning coefficient | learnCoef learnCoef.FactorAnalyses learnCoef.LatentForests learnCoef.MixtureModels learnCoef.ReducedRankRegressions |
| Multivariate gaussian log-likelihood. | logLike logLike.LatentForests |
| Maximum likelihood for data. | logLikeMle logLikeMle.BinomialMixtures logLikeMle.FactorAnalyses logLikeMle.GaussianMixtures logLikeMle.LatentForests logLikeMle.LCAs logLikeMle.ReducedRankRegressions |
| Help compute the MLE. | logLikeMleHelper logLikeMleHelper.ReducedRankRegressions |
| Linear collections of mixture models. | MixtureModels |
| Maximum likelihood estimator. | mle mle.BinomialMixtures mle.FactorAnalyses mle.GaussianMixtures mle.LatentForests mle.LCAs |
| Parents of a model. | parents parents.FactorAnalyses parents.LatentForests parents.MixtureModels parents.ReducedRankRegressions |
| Construct a poset of reduced rank regression models. | ReducedRankRegressions |
| Compute the sBIC. | sBIC |
| Set data for a model poset. | setData |
| Set data for the binomial mixture models. | setData.BinomialMixtures |
| Set data for the factor analysis models. | setData.FactorAnalyses |
| Set data for the gaussian mixture models. | setData.GaussianMixtures |
| Set data for the latent forest models. | setData.LatentForests |
| Set data for the LCA models. | setData.LCAs |
| Set data for the reduced rank regression models. | setData.ReducedRankRegressions |
| Set phi parameter. | setPhi setPhi.MixtureModels |