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mclust (version 5.4.5)

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.

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Version

Install

install.packages('mclust')

Monthly Downloads

58,836

Version

5.4.5

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

July 8th, 2019

Functions in mclust (5.4.5)

Mclust

Model-Based Clustering
dmvnorm

Density of multivariate Gaussian distribution
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
mclust-deprecated

Deprecated Functions in mclust package
cvMclustDA

MclustDA cross-validation
mclustICL

ICL Criterion for Model-Based Clustering
mclust-internal

Internal MCLUST functions
em

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

M-step for parameterized Gaussian mixture models
meE

EM algorithm starting with M-step for a parameterized Gaussian mixture model
clustCombi-internal

Internal clustCombi functions
EuroUnemployment

Unemployment data for European countries in 2014
GvHD

GvHD Dataset
partuniq

Classifies Data According to Unique Observations
plot.Mclust

Plotting method for Mclust model-based clustering
adjustedRandIndex

Adjusted Rand Index
clustCombi

Combining Gaussian Mixture Components for Clustering
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
chevron

Simulated minefield data
Baudry_etal_2010_JCGS_examples

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

Brier score to assess the accuracy of probabilistic predictions
clPairs

Pairwise Scatter Plots showing Classification
banknote

Swiss banknotes data
plot.mclustICL

ICL Plot for Model-Based Clustering
coordProj

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

Model-based Hierarchical Clustering
icl

ICL for an estimated Gaussian Mixture Model
dens

Density for Parameterized MVN Mixtures
hclass

Classifications from Hierarchical Agglomeration
densityMclust

Density Estimation via Model-Based Clustering
covw

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

Missing data imputation via the mix package
combiPlot

Plot Classifications Corresponding to Successive Combined Solutions
errorBars

Draw error bars on a plot
entPlot

Plot Entropy Plots
diabetes

Diabetes data
plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
plot.MclustDA

Plotting method for MclustDA discriminant analysis
summary.MclustDA

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

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

Indicator Variables given Classification
wdbc

Wisconsin diagnostic breast cancer (WDBC) data
mclustBICupdate

Update BIC values for parameterized Gaussian mixture models
mclustBIC

BIC for Model-Based Clustering
mstepE

M-step for a parameterized Gaussian mixture model
combiTree

Tree structure obtained from combining mixture components
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
mvn

Univariate or Multivariate Normal Fit
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
partconv

Numeric Encoding of a Partitioning
priorControl

Conjugate Prior for Gaussian Mixtures.
MclustDRsubsel

Subset selection for GMMDR directions based on BIC
emControl

Set control values for use with the EM algorithm
uncerPlot

Uncertainty Plot for Model-Based Clustering
thyroid

Thyroid gland data
wreath

Data Simulated from a 14-Component Mixture
cdensE

Component Density for a Parameterized MVN Mixture Model
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
clustCombiOptim

Optimal number of clusters obtained by combining mixture components
decomp2sigma

Convert mixture component covariances to matrix form
combMat

Combining Matrix
acidity

Acidity data
defaultPrior

Default conjugate prior for Gaussian mixtures
emE

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

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

E-step for parameterized Gaussian mixture models.
logLik.MclustDA

Log-Likelihood of a MclustDA object
logLik.Mclust

Log-Likelihood of a Mclust object
hc

Model-based Agglomerative Hierarchical Clustering
gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
imputePairs

Pairwise Scatter Plots showing Missing Data Imputations
MclustDA

MclustDA discriminant analysis
MclustDR

Dimension reduction for model-based clustering and classification
majorityVote

Majority vote
mclust-package

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

Plot one-dimensional data modeled by an MVN mixture.
mclust2Dplot

Plot two-dimensional data modelled by an MVN mixture
mvnX

Univariate or Multivariate Normal Fit
nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models
bic

BIC for Parameterized Gaussian Mixture Models
me

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

EM algorithm with weights starting with M-step for parameterized MVN mixture models
mclust.options

Default values for use with MCLUST package
cdens

Component Density for Parameterized MVN Mixture Models
hypvol

Aproximate Hypervolume for Multivariate Data
hdrlevels

Highest Density Region (HDR) Levels
mclustLoglik

Log-likelihood from a table of BIC values for parameterized Gaussian mixture models
map

Classification given Probabilities
mapClass

Correspondence between classifications
plot.MclustDR

Plotting method for dimension reduction for model-based clustering and classification
randProj

Random projections of multidimensional data modeled by an MVN mixture
plot.clustCombi

Plot Combined Clusterings Results
randomOrthogonalMatrix

Random orthogonal matrix
surfacePlot

Density or uncertainty surface for bivariate mixtures
summary.mclustBIC

Summary function for model-based clustering via BIC
plot.densityMclust

Plots for Mixture-Based Density Estimate
predict.MclustDR

Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
plot.mclustBIC

BIC Plot for Model-Based Clustering
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
mclustModel

Best model based on BIC
mclustVariance

Template for variance specification for parameterized Gaussian mixture models
mclustModelNames

MCLUST Model Names
randomPairs

Random hierarchical structure
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
sigma2decomp

Convert mixture component covariances to decomposition form.
simE

Simulate from a Parameterized MVN Mixture Model
sim

Simulate from Parameterized MVN Mixture Models
MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models
classError

Classification error
classPriorProbs

Estimation of class prior probabilities by EM algorithm
cross

Simulated Cross Data