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mclust (version 2.1-14)

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

59,191

Version

2.1-14

License

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

Maintainer

Chris Fraley interim

Last Published

February 23rd, 2024

Functions in mclust (2.1-14)

Mclust

Model-Based Clustering
cv1EMtrain

Select discriminant models using cross validation
mapClass

Correspondence between classifications.
hypvol

Aproximate Hypervolume for Multivariate Data
bicEMtrain

Select models in discriminant analysis using BIC
map

Classification given Probabilities
density

Kernel Density Estimation
EMclust

BIC for Model-Based Clustering
cdensE

Component Density for a Parameterized MVN Mixture Model
compareClass

Compare classifications.
estepE

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

Model-based Hierarchical Clustering
bic

BIC for Parameterized MVN Mixture Models
summary.mclustDAtest

Classification and posterior probability from mclustDAtest.
classError

Classification error.
grid1

Generate grid points
hclass

Classifications from Hierarchical Agglomeration
cdens

Component Density for Parameterized MVN Mixture Models
clPairs

Pairwise Scatter Plots showing Classification
meE

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

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

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

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

E-step for parameterized MVN mixture models.
coordProj

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

Density for Parameterized MVN Mixtures
partconv

Convert partitioning into numerical vector.
summary.EMclustN

summary function for EMclustN
decomp2sigma

Convert mixture component covariances to matrix form.
bicE

BIC for a Parameterized MVN Mixture Model
unmap

Indicator Variables given Classification
sigma2decomp

Convert mixture component covariances to decomposition form.
plot.Mclust

Plot Model-Based Clustering Results
plot.mclustDA

Plotting method for MclustDA discriminant analysis.
Defaults.Mclust

List of values controlling defaults for some MCLUST functions.
hc

Model-based Hierarchical Clustering
summary.EMclust

Summary function for EMclust
uncerPlot

Uncertainty Plot for Model-Based Clustering
mclust1Dplot

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

Simulate from Parameterized MVN Mixture Models
mclustDAtest

MclustDA Testing
spinProj

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

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

Multivariate Normal Fit
summary.mclustDAtrain

Models and classifications from mclustDAtrain
mclustDAtrain

MclustDA Training
mvn

Multivariate Normal Fit
partuniq

Classifies Data According to Unique Observations
mclust2Dplot

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

Set control values for use with MCLUST.
mclust-internal

Internal MCLUST functions
em

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

Very brief summary of an Mclust object.
simE

Simulate from a Parameterized MVN Mixture Model
mclustDA

MclustDA discriminant analysis.
EMclustN

BIC for Model-Based Clustering with Poisson Noise
randProj

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

Density or uncertainty surface for two dimensional mixtures.
lansing

Maple trees in Lansing Woods
diabetes

Diabetes data
chevron

Simulated minefield data