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mclust (version 2.1-8)

Model-based cluster analysis

Description

Model-based cluster analysis: the 2002 version of MCLUST

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Version

Install

install.packages('mclust')

Monthly Downloads

74,509

Version

2.1-8

License

See http://www.stat.washington.edu/mclust/license.txt

Maintainer

Ron Wehrens

Last Published

February 23rd, 2024

Functions in mclust (2.1-8)

cdens

Component Density for Parameterized MVN Mixture Models
hclass

Classifications from Hierarchical Agglomeration
mvnX

Multivariate Normal Fit
estepE

E-step in the EM algorithm for a parameterized MVN mixture model.
clPairs

Pairwise Scatter Plots showing Classification
partuniq

Classifies Data According to Unique Observations
Mclust

Model-Based Clustering
bicE

BIC for a Parameterized MVN Mixture Model
summary.EMclust

Summary function for EMclust
compareClass

Compare classifications.
emE

EM algorithm starting with E-step for a parameterized MVN mixture model.
hypvol

Aproximate Hypervolume for Multivariate Data
plot.mclustDA

Plotting method for MclustDA discriminant analysis.
surfacePlot

Density or uncertainty surface for two dimensional mixtures.
summary.mclustDAtest

Classification and posterior probability from mclustDAtest.
partconv

Convert partitioning into numerical vector.
cv1EMtrain

Select discriminant models using cross validation
decomp2sigma

Convert mixture component covariances to matrix form.
randProj

Random projections for data in more than two dimensions modelled by an MVN mixture.
meE

EM algorithm starting with M-step for a parameterized MVN mixture model.
hc

Model-based Hierarchical Clustering
bicEMtrain

Select models in discriminant analysis using BIC
mclust-internal

Internal MCLUST functions
bic

BIC for Parameterized MVN Mixture Models
dens

Density for Parameterized MVN Mixtures
mclustDAtest

MclustDA Testing
map

Classification given Probabilities
EMclustN

BIC for Model-Based Clustering with Poisson Noise
hcE

Model-based Hierarchical Clustering
mclust2Dplot

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

Classification error.
me

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

Correspondence between classifications.
mclustDA

MclustDA discriminant analysis.
sigma2decomp

Convert mixture component covariances to decomposition form.
spinProj

Planar spin for random projections of data in more than two dimensions modelled by an MVN mixture.
mvn

Multivariate Normal Fit
Defaults.Mclust

List of values controlling defaults for some MCLUST functions.
unmap

Indicator Variables given Classification
mclustOptions

Set control values for use with MCLUST.
density

Kernel Density Estimation
estep

E-step for parameterized MVN mixture models.
plot.Mclust

Plot Model-Based Clustering Results
summary.mclustDAtrain

Models and classifications from mclustDAtrain
sim

Simulate from Parameterized MVN Mixture Models
simE

Simulate from a Parameterized MVN Mixture Model
summary.EMclustN

summary function for EMclustN
grid1

Generate grid points
mstepE

M-step in the EM algorithm for a parameterized MVN mixture model.
mclustDAtrain

MclustDA Training
mstep

M-step in the EM algorithm for parameterized MVN mixture models.
uncerPlot

Uncertainty Plot for Model-Based Clustering
summary.Mclust

Very brief summary of an Mclust object.
coordProj

Coordinate projections of data in more than two dimensions modelled by an MVN mixture.
em

EM algorithm starting with E-step for parameterized MVN mixture models.
mclust1Dplot

Plot one-dimensional data modelled by an MVN mixture.
EMclust

BIC for Model-Based Clustering
cdensE

Component Density for a Parameterized MVN Mixture Model
lansing

Maple trees in Lansing Woods
diabetes

Diabetes data
chevron

Simulated minefield data