mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

AuthorChris Fraley [aut], Adrian E. Raftery [aut], Luca Scrucca [aut, cre], Thomas Brendan Murphy [ctb], Michael Fop [ctb]
Date of publication2017-01-03 17:09:07
MaintainerLuca Scrucca <luca.scrucca@unipg.it>
LicenseGPL (>= 2)
Version5.2.1
http://www.stat.washington.edu/mclust/

View on CRAN

Man pages

acidity: Acidity data

adjustedRandIndex: Adjusted Rand Index

banknote: Swiss banknotes data

Baudry_etal_2010_JCGS_examples: Simulated Example Datasets From Baudry et al. (2010)

bic: BIC for Parameterized Gaussian Mixture Models

cdens: Component Density for Parameterized MVN Mixture Models

cdensE: Component Density for a Parameterized MVN Mixture Model

cdfMclust: Cumulative Distribution and Quantiles for a univariate...

chevron: Simulated minefield data

classError: Classification error

clPairs: Pairwise Scatter Plots showing Classification

clustCombi: Combining Gaussian Mixture Components for Clustering

clustCombi-internals: Internal clustCombi functions

combiPlot: Plot Classifications Corresponding to Successive Combined...

combMat: Combining Matrix

coordProj: Coordinate projections of multidimensional data modeled by an...

covw: Weighted means, covariance and scattering matrices...

cross: Simulated Cross Data

cvMclustDA: MclustDA cross-validation

decomp2sigma: Convert mixture component covariances to matrix form.

defaultPrior: Default conjugate prior for Gaussian mixtures.

dens: Density for Parameterized MVN Mixtures

densityMclust: Density Estimation via Model-Based Clustering

densityMclust.diagnostic: Diagnostic plots for 'mclustDensity' estimation

diabetes: Diabetes data

em: EM algorithm starting with E-step for parameterized Gaussian...

emControl: Set control values for use with the EM algorithm.

emE: EM algorithm starting with E-step for a parameterized...

entPlot: Plot Entropy Plots

errorBars: Draw error bars on a plot

estep: E-step for parameterized Gaussian mixture models.

estepE: E-step in the EM algorithm for a parameterized Gaussian...

GvHD: GvHD Dataset

hc: Model-based Hierarchical Clustering

hcE: Model-based Hierarchical Clustering

hclass: Classifications from Hierarchical Agglomeration

hypvol: Aproximate Hypervolume for Multivariate Data

icl: ICL for an estimated Gaussian Mixture Model

imputeData: Missing Data Imputation via the 'mix' package

imputePairs: Pairwise Scatter Plots showing Missing Data Imputations

logLik.Mclust: Log-Likelihood of a 'Mclust' object

logLik.MclustDA: Log-Likelihood of a 'MclustDA' object

map: Classification given Probabilities

mapClass: Correspondence between classifications.

Mclust: Model-Based Clustering

mclust1Dplot: Plot one-dimensional data modeled by an MVN mixture.

mclust2Dplot: Plot two-dimensional data modelled by an MVN mixture.

mclustBIC: BIC for Model-Based Clustering

MclustBootstrap: Resampling-based Inference for Gaussian finite mixture models

mclustBootstrapLRT: Bootstrap Likelihood Ratio Test for the Number of Mixture...

MclustDA: MclustDA discriminant analysis

mclust-deprecated: Deprecated Functions in mclust package

MclustDR: Dimension reduction for model-based clustering and...

mclustICL: ICL Criterion for Model-Based Clustering

mclust-internal: Internal MCLUST functions

mclustModel: Best model based on BIC

mclustModelNames: MCLUST Model Names

mclust.options: Default values for use with MCLUST package

mclust-package: Normal Mixture Modeling for Model-Based Clustering,...

mclustVariance: Template for variance specification for parameterized...

me: EM algorithm starting with M-step for parameterized MVN...

meE: EM algorithm starting with M-step for a parameterized...

me.weighted: EM algorithm with weights starting with M-step for...

mstep: M-step for parameterized Gaussian mixture models.

mstepE: M-step for a parameterized Gaussian mixture model.

mvn: Univariate or Multivariate Normal Fit

mvnX: Univariate or Multivariate Normal Fit

nMclustParams: Number of Estimated Parameters in Gaussian Mixture Models

nVarParams: Number of Variance Parameters in Gaussian Mixture Models

partconv: Numeric Encoding of a Partitioning

partuniq: Classifies Data According to Unique Observations

plot.clustCombi: Plot Combined Clusterings Results

plot.densityMclust: Plots for Mixture-Based Density Estimate

plot.Mclust: Plot Model-Based Clustering Results

plot.mclustBIC: BIC Plot for Model-Based Clustering

plot.MclustBoostrap: Plot of bootstrap distributions for mixture model parameters

plot.MclustDA: Plotting method for MclustDA discriminant analysis

plot.MclustDR: Plotting method for dimension reduction for model-based...

plot.mclustICL: ICL Plot for Model-Based Clustering

predict.densityMclust: Density estimate of multivariate observations by Gaussian...

predict.Mclust: Cluster multivariate observations by Gaussian finite mixture...

predict.MclustDA: Classify multivariate observations by Gaussian finite mixture...

predict.MclustDR: Classify multivariate observations on a dimension reduced...

print.clustCombi: Displays Combined Clusterings Results

priorControl: Conjugate Prior for Gaussian Mixtures.

randomPairs: Random hierarchical structure

randProj: Random projections of multidimensional data modeled by an MVN...

sigma2decomp: Convert mixture component covariances to decomposition form.

sim: Simulate from Parameterized MVN Mixture Models

simE: Simulate from a Parameterized MVN Mixture Model

summary.Mclust: Summarizing Gaussian Finite Mixture Model Fits

summary.mclustBIC: Summary function for model-based clustering via BIC

summary.MclustBootstrap: Summary Function for Bootstrap Inference for Gaussian Finite...

summary.MclustDA: Summarizing discriminant analysis based on Gaussian finite...

summary.MclustDR: Summarizing dimension reduction method for model-based...

surfacePlot: Density or uncertainty surface for bivariate mixtures.

thyroid: Thyroid gland data

uncerPlot: Uncertainty Plot for Model-Based Clustering

unmap: Indicator Variables given Classification

wreath: Data Simulated from a 14-Component Mixture

Files in this package

mclust
mclust/inst
mclust/inst/CITATION
mclust/inst/NEWS
mclust/inst/doc
mclust/inst/doc/mclust.R
mclust/inst/doc/mclust.Rmd
mclust/inst/doc/index.html
mclust/inst/doc/mclust4.pdf
mclust/inst/doc/mclust-weights.pdf
mclust/inst/doc/mclust.html
mclust/src
mclust/src/Makevars
mclust/src/mclustaddson.f
mclust/src/mclust.f
mclust/NAMESPACE
mclust/data
mclust/data/Baudry_etal_2010_JCGS_examples.rda
mclust/data/acidity.rda
mclust/data/thyroid.rda
mclust/data/chevron.rda
mclust/data/GvHD.rda
mclust/data/wreath.rda
mclust/data/cross.rda
mclust/data/diabetes.rda
mclust/data/banknote.txt.gz
mclust/R
mclust/R/mclust.R mclust/R/mclustdr.R mclust/R/bootstrap.R mclust/R/mclustaddson.R mclust/R/densityMclust.R mclust/R/mclustda.R mclust/R/icl.R mclust/R/weights.R mclust/R/clustCombi.R mclust/R/options.R mclust/R/init.R mclust/R/util.R mclust/R/zzz.R
mclust/vignettes
mclust/vignettes/mclust.Rmd
mclust/MD5
mclust/build
mclust/build/vignette.rds
mclust/DESCRIPTION
mclust/man
mclust/man/em.Rd mclust/man/simE.Rd mclust/man/acidity.Rd mclust/man/surfacePlot.Rd mclust/man/me.Rd mclust/man/logLik.MclustDA.Rd mclust/man/dens.Rd mclust/man/meE.Rd mclust/man/densityMclust.Rd mclust/man/hypvol.Rd mclust/man/clustCombi.Rd mclust/man/plot.densityMclust.Rd mclust/man/mclustVariance.Rd mclust/man/plot.MclustDR.Rd mclust/man/estep.Rd mclust/man/chevron.Rd mclust/man/map.Rd mclust/man/mclust-package.Rd mclust/man/mclust2Dplot.Rd mclust/man/partuniq.Rd mclust/man/plot.clustCombi.Rd mclust/man/classError.Rd mclust/man/wreath.Rd mclust/man/logLik.Mclust.Rd mclust/man/mclustBIC.Rd mclust/man/combMat.Rd mclust/man/Baudry_etal_2010_JCGS_examples.Rd mclust/man/MclustBootstrap.Rd mclust/man/mclustICL.Rd mclust/man/mvnX.Rd mclust/man/plot.mclustBIC.Rd mclust/man/errorBars.Rd mclust/man/priorControl.Rd mclust/man/mstepE.Rd mclust/man/estepE.Rd mclust/man/cross.Rd mclust/man/clustCombi-internals.Rd mclust/man/hclass.Rd mclust/man/mclustBootstrapLRT.Rd mclust/man/adjustedRandIndex.Rd mclust/man/imputePairs.Rd mclust/man/mclustModelNames.Rd mclust/man/randProj.Rd mclust/man/summary.mclustBIC.Rd mclust/man/mapClass.Rd mclust/man/emE.Rd mclust/man/summary.Mclust.Rd mclust/man/bic.Rd mclust/man/emControl.Rd mclust/man/cdensE.Rd mclust/man/randomPairs.Rd mclust/man/partconv.Rd mclust/man/mclust-internal.Rd mclust/man/entPlot.Rd mclust/man/GvHD.Rd mclust/man/predict.Mclust.Rd mclust/man/decomp2sigma.Rd mclust/man/MclustDA.Rd mclust/man/mstep.Rd mclust/man/print.clustCombi.Rd mclust/man/nVarParams.Rd mclust/man/predict.MclustDR.Rd mclust/man/cdens.Rd mclust/man/unmap.Rd mclust/man/mclustModel.Rd mclust/man/hcE.Rd mclust/man/hc.Rd mclust/man/coordProj.Rd mclust/man/cdfMclust.Rd mclust/man/densityMclust.diagnostic.Rd mclust/man/cvMclustDA.Rd mclust/man/combiPlot.Rd mclust/man/mclust1Dplot.Rd mclust/man/clPairs.Rd mclust/man/banknote.Rd mclust/man/plot.mclustICL.Rd mclust/man/covw.Rd mclust/man/summary.MclustDR.Rd mclust/man/predict.MclustDA.Rd mclust/man/thyroid.Rd mclust/man/Mclust.Rd mclust/man/plot.MclustDA.Rd mclust/man/mvn.Rd mclust/man/imputeData.Rd mclust/man/diabetes.Rd mclust/man/MclustDR.Rd mclust/man/summary.MclustDA.Rd mclust/man/summary.MclustBootstrap.Rd mclust/man/plot.Mclust.Rd mclust/man/uncerPlot.Rd mclust/man/sigma2decomp.Rd mclust/man/nMclustParams.Rd mclust/man/mclust.options.Rd mclust/man/icl.Rd mclust/man/me.weighted.Rd mclust/man/mclust-deprecated.Rd mclust/man/plot.MclustBoostrap.Rd mclust/man/sim.Rd mclust/man/predict.densityMclust.Rd mclust/man/defaultPrior.Rd

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