Learn R Programming
⚠️There's a newer version (6.1) of this package.Take me there.

mclust (version 5.4)

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

Description

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.

Copy Link

Version

Install

install.packages('mclust')

Monthly Downloads

57,181

Version

5.4

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

November 22nd, 2017

Functions in mclust (5.4)

banknote

Swiss banknotes data
acidity

Acidity data
MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models
MclustDA

MclustDA discriminant analysis
adjustedRandIndex

Adjusted Rand Index
MclustDRsubsel

Subset selection for GMMDR directions based on BIC.
Baudry_etal_2010_JCGS_examples

Simulated Example Datasets From Baudry et al. (2010)
Mclust

Model-Based Clustering
GvHD

GvHD Dataset
MclustDR

Dimension reduction for model-based clustering and classification
cdens

Component Density for Parameterized MVN Mixture Models
classError

Classification error
clustCombi-internal

Internal clustCombi functions
cdensE

Component Density for a Parameterized MVN Mixture Model
bic

BIC for Parameterized Gaussian Mixture Models
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
chevron

Simulated minefield data
clPairs

Pairwise Scatter Plots showing Classification
combMat

Combining Matrix
clustCombi

Combining Gaussian Mixture Components for Clustering
combiPlot

Plot Classifications Corresponding to Successive Combined Solutions
clustCombiOptim

Optimal number of clusters obtained by combining mixture components
defaultPrior

Default conjugate prior for Gaussian mixtures.
covw

Weighted means, covariance and scattering matrices conditioning on a weighted matrix.
cross

Simulated Cross Data
dens

Density for Parameterized MVN Mixtures
combiTree

Tree structure obtained from combining mixture components
densityMclust

Density Estimation via Model-Based Clustering
coordProj

Coordinate projections of multidimensional data modeled by an MVN mixture.
diabetes

Diabetes data
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
em

EM algorithm starting with E-step for parameterized Gaussian mixture models.
imputeData

Missing data imputation via the mix package
gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
hc

Model-based Hierarchical Clustering
imputePairs

Pairwise Scatter Plots showing Missing Data Imputations
emControl

Set control values for use with the EM algorithm.
cvMclustDA

MclustDA cross-validation
emE

EM algorithm starting with E-step for a parameterized Gaussian mixture model.
decomp2sigma

Convert mixture component covariances to matrix form.
logLik.Mclust

Log-Likelihood of a Mclust object
logLik.MclustDA

Log-Likelihood of a MclustDA object
estep

E-step for parameterized Gaussian mixture models.
entPlot

Plot Entropy Plots
estepE

E-step in the EM algorithm for a parameterized Gaussian mixture model.
errorBars

Draw error bars on a plot
hcE

Model-based Hierarchical Clustering
hypvol

Aproximate Hypervolume for Multivariate Data
hclass

Classifications from Hierarchical Agglomeration
icl

ICL for an estimated Gaussian Mixture Model
majorityVote

Majority vote
mclust-internal

Internal MCLUST functions
mclust.options

Default values for use with MCLUST package
mclust-package

Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
mclust1Dplot

Plot one-dimensional data modeled by an MVN mixture.
me.weighted

EM algorithm with weights starting with M-step for parameterized MVN mixture models
mclust2Dplot

Plot two-dimensional data modelled by an MVN mixture.
meE

EM algorithm starting with M-step for a parameterized Gaussian mixture model.
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
mclustBIC

BIC for Model-Based Clustering
mclustICL

ICL Criterion for Model-Based Clustering
map

Classification given Probabilities
partconv

Numeric Encoding of a Partitioning
plot.Mclust

Plot Model-Based Clustering Results
mstep

M-step for parameterized Gaussian mixture models.
plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters
mstepE

M-step for a parameterized Gaussian mixture model.
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
predict.MclustDR

Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
partuniq

Classifies Data According to Unique Observations
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
mapClass

Correspondence between classifications.
plot.MclustDA

Plotting method for MclustDA discriminant analysis
mclust-deprecated

Deprecated Functions in mclust package
plot.MclustDR

Plotting method for dimension reduction for model-based clustering and classification
plot.mclustBIC

BIC Plot for Model-Based Clustering
mclustVariance

Template for variance specification for parameterized Gaussian mixture models
plot.mclustICL

ICL Plot for Model-Based Clustering
me

EM algorithm starting with M-step for parameterized MVN mixture models.
randomPairs

Random hierarchical structure
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
mclustModel

Best model based on BIC
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
mclustModelNames

MCLUST Model Names
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models
sigma2decomp

Convert mixture component covariances to decomposition form.
mvn

Univariate or Multivariate Normal Fit
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
mvnX

Univariate or Multivariate Normal Fit
priorControl

Conjugate Prior for Gaussian Mixtures.
plot.clustCombi

Plot Combined Clusterings Results
sim

Simulate from Parameterized MVN Mixture Models
plot.densityMclust

Plots for Mixture-Based Density Estimate
summary.mclustBIC

Summary function for model-based clustering via BIC
simE

Simulate from a Parameterized MVN Mixture Model
surfacePlot

Density or uncertainty surface for bivariate mixtures.
unmap

Indicator Variables given Classification
randProj

Random projections of multidimensional data modeled by an MVN mixture.
wreath

Data Simulated from a 14-Component Mixture
summary.MclustDA

Summarizing discriminant analysis based on Gaussian finite mixture modeling.
summary.MclustDR

Summarizing dimension reduction method for model-based clustering and classification
thyroid

Thyroid gland data
uncerPlot

Uncertainty Plot for Model-Based Clustering