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mclust (version 5.2.2)

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

55,830

Version

5.2.2

License

GPL (>= 2)

Maintainer

Luca Scrucca

Last Published

January 22nd, 2017

Functions in mclust (5.2.2)

classError

Classification error
adjustedRandIndex

Adjusted Rand Index
chevron

Simulated minefield data
clPairs

Pairwise Scatter Plots showing Classification
cdens

Component Density for Parameterized MVN Mixture Models
cdensE

Component Density for a Parameterized MVN Mixture Model
acidity

Acidity data
clustCombi

Combining Gaussian Mixture Components for Clustering
cross

Simulated Cross Data
clustCombi-internal

Internal clustCombi functions
cvMclustDA

MclustDA cross-validation
combiPlot

Plot Classifications Corresponding to Successive Combined Solutions
combMat

Combining Matrix
densityMclust

Density Estimation via Model-Based Clustering
covw

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

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

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

Convert mixture component covariances to matrix form.
dens

Density for Parameterized MVN Mixtures
densityMclust.diagnostic

Diagnostic plots for mclustDensity estimation
defaultPrior

Default conjugate prior for Gaussian mixtures.
estepE

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

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

Log-Likelihood of a Mclust object
errorBars

Draw error bars on a plot
entPlot

Plot Entropy Plots
logLik.MclustDA

Log-Likelihood of a MclustDA object
hcE

Model-based Hierarchical Clustering
GvHD

GvHD Dataset
hc

Model-based Hierarchical Clustering
hclass

Classifications from Hierarchical Agglomeration
mclust-internal

Internal MCLUST functions
mclust-deprecated

Deprecated Functions in mclust package
mclust-package

Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation
hypvol

Aproximate Hypervolume for Multivariate Data
Mclust

Model-Based Clustering
icl

ICL for an estimated Gaussian Mixture Model
map

Classification given Probabilities
mclust.options

Default values for use with MCLUST package
mapClass

Correspondence between classifications.
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
MclustDA

MclustDA discriminant analysis
meE

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

Dimension reduction for model-based clustering and classification
mvn

Univariate or Multivariate Normal Fit
nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models
emControl

Set control values for use with the EM algorithm.
imputeData

Missing Data Imputation via the mix package
emE

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

Pairwise Scatter Plots showing Missing Data Imputations
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
partuniq

Classifies Data According to Unique Observations
mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components
plot.clustCombi

Plot Combined Clusterings Results
plot.mclustBIC

BIC Plot for Model-Based Clustering
nVarParams

Number of Variance Parameters in Gaussian Mixture Models
plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters
plot.mclustICL

ICL Plot for Model-Based Clustering
partconv

Numeric Encoding of a Partitioning
predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling
summary.mclustBIC

Summary function for model-based clustering via BIC
summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits
simE

Simulate from a Parameterized MVN Mixture Model
sim

Simulate from Parameterized MVN Mixture Models
plot.densityMclust

Plots for Mixture-Based Density Estimate
predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling
plot.Mclust

Plot Model-Based Clustering Results
summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling
summary.MclustDA

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

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

Density or uncertainty surface for bivariate mixtures.
Baudry_etal_2010_JCGS_examples

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

BIC for Parameterized Gaussian Mixture Models
mclustICL

ICL Criterion for Model-Based Clustering
cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution
mclustModel

Best model based on BIC
mstep

M-step for parameterized Gaussian mixture models.
predict.MclustDR

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

M-step for a parameterized Gaussian mixture model.
print.clustCombi

Displays Combined Clusterings Results
uncerPlot

Uncertainty Plot for Model-Based Clustering
sigma2decomp

Convert mixture component covariances to decomposition form.
randProj

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

Indicator Variables given Classification
mclustVariance

Template for variance specification for parameterized Gaussian mixture models
me

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

Plotting method for MclustDA discriminant analysis
priorControl

Conjugate Prior for Gaussian Mixtures.
plot.MclustDR

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

Data Simulated from a 14-Component Mixture
randomPairs

Random hierarchical structure