bgmm: Gaussian Mixture Modeling Algorithms And The Belief-based Mixture Modeling

Two partially supervised mixture modeling methods: soft-label and belief-based modeling are implemented. For completeness, we equipped the package also with the functionality of unsupervised, semi- and fully supervised mixture modeling. The package can be applied also to selection of the best-fitting from a set of models with different component numbers or constraints on their structures. For detailed introduction see: Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy Tiuryn (2012), The R Package bgmm: Mixture Modeling with Uncertain Knowledge, Journal of Statistical Software.

Author
Przemyslaw Biecek \& Ewa Szczurek
Date of publication
2014-12-19 15:57:54
Maintainer
Przemyslaw Biecek <Przemyslaw.Biecek@gmail.com>
License
GPL-3
Version
1.7
URLs

View on CRAN

Man pages

bgmm-package
Belief-based Gaussian mixture modeling
CellCycle
Data for clustering of 384 cell cycle genes into five...
chooseModels
Selecting a subset of fitted models
crossval
k-fold cross-validation for the specified model
DEprobs
Signed probabilities of differential expression
genotypes
Fluorescence signals corresponding to a given allele for 333...
getModelStructure
Model structure
init.model.params
Initiation of model parameters
miRNA
miRNA transfection data for miR1 and miR124 target genes
mModel
Fitting Gaussian mixture model
mModelList
Fitting Gaussian mixture model or collection of models
plotGIC
Plotting GIC scores
plot.mModel
Plotting a graphical visualization of a Gaussian model or a...
plot.mModelList
Plotting a graphical visualization of a model or a list of...
predict.mModel
Predictions for fitted Gaussian component model
simulateData
Dataset generation
Ste12
Ste12 knockout data under pheromone treatment versus wild...
tools
Set of supplementary functions for bgmm package

Files in this package

bgmm
bgmm/inst
bgmm/inst/CITATION
bgmm/NAMESPACE
bgmm/demo
bgmm/demo/00Index
bgmm/demo/bgmm.r
bgmm/data
bgmm/data/CellCycle.RData
bgmm/data/genotypes.RData
bgmm/data/Ste12.RData
bgmm/data/miRNA.RData
bgmm/R
bgmm/R/soft.e.step.r
bgmm/R/bgmm.m.step.r
bgmm/R/semiList.r
bgmm/R/clusterAssigment.r
bgmm/R/get.simple.beliefs.r
bgmm/R/soft.r
bgmm/R/getModelSettings.r
bgmm/R/plot.bgmm.r
bgmm/R/bgmm.e.step.r
bgmm/R/bgmm.r
bgmm/R/plot.semiList.r
bgmm/R/getSimulatedKdimensionalData.r
bgmm/R/DEprobs.r
bgmm/README.md
bgmm/MD5
bgmm/DESCRIPTION
bgmm/man
bgmm/man/plot.mModel.Rd
bgmm/man/chooseModels.Rd
bgmm/man/plot.mModelList.Rd
bgmm/man/tools.Rd
bgmm/man/getModelStructure.Rd
bgmm/man/miRNA.Rd
bgmm/man/init.model.params.Rd
bgmm/man/plotGIC.Rd
bgmm/man/mModel.Rd
bgmm/man/genotypes.Rd
bgmm/man/bgmm-package.Rd
bgmm/man/predict.mModel.Rd
bgmm/man/Ste12.Rd
bgmm/man/mModelList.Rd
bgmm/man/DEprobs.Rd
bgmm/man/simulateData.Rd
bgmm/man/crossval.Rd
bgmm/man/CellCycle.Rd