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mclust (version 5.4.2)

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

74,509

Version

5.4.2

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

November 17th, 2018

Functions in mclust (5.4.2)

bic

BIC for Parameterized Gaussian Mixture Models
cdensE

Component Density for a Parameterized MVN Mixture Model
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
defaultPrior

Default conjugate prior for Gaussian mixtures.
hypvol

Aproximate Hypervolume for Multivariate Data
dens

Density for Parameterized MVN Mixtures
mclust-package

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

Highest Density Region (HDR) Levels
densityMclust

Density Estimation via Model-Based Clustering
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
cdens

Component Density for Parameterized MVN Mixture Models
mclust.options

Default values for use with MCLUST package
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
mclustICL

ICL Criterion for Model-Based Clustering
chevron

Simulated minefield data
MclustDR

Dimension reduction for model-based clustering and classification
classError

Classification error
partuniq

Classifies Data According to Unique Observations
covw

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

Pairwise Scatter Plots showing Classification
plot.Mclust

Plot Model-Based Clustering Results
clustCombi-internal

Internal clustCombi functions
cross

Simulated Cross Data
clustCombi

Combining Gaussian Mixture Components for Clustering
combiTree

Tree structure obtained from combining mixture components
emControl

Set control values for use with the EM algorithm.
clustCombiOptim

Optimal number of clusters obtained by combining mixture components
combMat

Combining Matrix
emE

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

Plots for Mixture-Based Density Estimate
coordProj

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

Plot Classifications Corresponding to Successive Combined Solutions
plot.mclustBIC

BIC Plot for Model-Based Clustering
sigma2decomp

Convert mixture component covariances to decomposition form.
cvMclustDA

MclustDA cross-validation
sim

Simulate from Parameterized MVN Mixture Models
decomp2sigma

Convert mixture component covariances to matrix form.
estep

E-step for parameterized Gaussian mixture models.
entPlot

Plot Entropy Plots
diabetes

Diabetes data
summary.MclustDR

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

Pairwise Scatter Plots showing Missing Data Imputations
logLik.Mclust

Log-Likelihood of a Mclust object
mclust-deprecated

Deprecated Functions in mclust package
errorBars

Draw error bars on a plot
summary.mclustBIC

Summary function for model-based clustering via BIC
estepE

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

Model-based Hierarchical Clustering
mclust-internal

Internal MCLUST functions
hclass

Classifications from Hierarchical Agglomeration
mclustModelNames

MCLUST Model Names
majorityVote

Majority vote
logLik.MclustDA

Log-Likelihood of a MclustDA object
em

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

ICL for an estimated Gaussian Mixture Model
me

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

Template for variance specification for parameterized Gaussian mixture models
imputeData

Missing data imputation via the mix package
gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
mstepE

M-step for a parameterized Gaussian mixture model.
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.
mclust1Dplot

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

Univariate or Multivariate Normal Fit
mvn

Univariate or Multivariate Normal Fit
nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models
mclustBIC

BIC for Model-Based Clustering
plot.MclustDR

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

Plot of bootstrap distributions for mixture model parameters
mclustBICupdate

Update BIC values for parameterized Gaussian mixture models
plot.MclustDA

Plotting method for MclustDA discriminant analysis
meE

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

ICL Plot for Model-Based Clustering
mstep

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

Plot Combined Clusterings Results
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
randProj

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

Model-based Hierarchical Clustering
map

Classification given Probabilities
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
uncerPlot

Uncertainty Plot for Model-Based Clustering
surfacePlot

Density or uncertainty surface for bivariate mixtures
summary.MclustDA

Summarizing discriminant analysis based on Gaussian finite mixture modeling.
priorControl

Conjugate Prior for Gaussian Mixtures.
thyroid

Thyroid gland data
randomPairs

Random hierarchical structure
unmap

Indicator Variables given Classification
wreath

Data Simulated from a 14-Component Mixture
mapClass

Correspondence between classifications.
mclustLoglik

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

Best model based on BIC
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
partconv

Numeric Encoding of a Partitioning
predict.MclustDR

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

Simulate from a Parameterized MVN Mixture Model
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
MclustDA

MclustDA discriminant analysis
Mclust

Model-Based Clustering
adjustedRandIndex

Adjusted Rand Index
MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models
MclustDRsubsel

Subset selection for GMMDR directions based on BIC.
banknote

Swiss banknotes data
acidity

Acidity data
Baudry_etal_2010_JCGS_examples

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

GvHD Dataset