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mclust (version 2.1-5)
Model-based cluster analysis
Description
Model-based cluster analysis: the 2002 version of MCLUST
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Install
install.packages('mclust')
Monthly Downloads
74,509
Version
2.1-5
License
See http://www.stat.washington.edu/mclust/license.txt
Maintainer
University of Washington R port by Ron Wehrens
Last Published
February 23rd, 2024
Functions in mclust (2.1-5)
Search all functions
coordProj
Coordinate projections of data in more than two dimensions modelled by an MVN mixture.
me
EM algorithm starting with M-step for parameterized MVN mixture models.
classError
Classification error.
EMclustN
BIC for Model-Based Clustering with Poisson Noise
Mclust
Model-Based Clustering
EMclust
BIC for Model-Based Clustering
bic
BIC for Parameterized MVN Mixture Models
mclustDAtest
MclustDA Testing
unmap
Indicator Variables given Classification
em
EM algorithm starting with E-step for parameterized MVN mixture models.
Defaults.Mclust
List of values controlling defaults for some MCLUST functions.
cv1EMtrain
Select discriminant models using cross validation
bicE
BIC for a Parameterized MVN Mixture Model
summary.mclustDAtrain
Models and classifications from mclustDAtrain
hypvol
Aproximate Hypervolume for Multivariate Data
mclustDA
MclustDA discriminant analysis.
mstepE
M-step in the EM algorithm for a parameterized MVN mixture model.
mclustOptions
Set control values for use with MCLUST.
summary.Mclust
Very brief summary of an Mclust object.
mvnX
Multivariate Normal Fit
plot.mclustDA
Plotting method for MclustDA discriminant analysis.
estep
E-step for parameterized MVN mixture models.
sigma2decomp
Convert mixture component covariances to decomposition form.
hc
Model-based Hierarchical Clustering
density
Kernel Density Estimation
clPairs
Pairwise Scatter Plots showing Classification
decomp2sigma
Convert mixture component covariances to matrix form.
estepE
E-step in the EM algorithm for a parameterized MVN mixture model.
compareClass
Compare classifications.
simE
Simulate from a Parameterized MVN Mixture Model
partuniq
Classifies Data According to Unique Observations
map
Classification given Probabilities
summary.mclustDAtest
Classification and posterior probability from mclustDAtest.
summary.EMclustN
summary function for EMclustN
mstep
M-step in the EM algorithm for parameterized MVN mixture models.
spinProj
Planar spin for random projections of data in more than two dimensions modelled by an MVN mixture.
cdensE
Component Density for a Parameterized MVN Mixture Model
dens
Density for Parameterized MVN Mixtures
sim
Simulate from Parameterized MVN Mixture Models
surfacePlot
Density or uncertainty surface for two dimensional mixtures.
mclust1Dplot
Plot one-dimensional data modelled by an MVN mixture.
plot.Mclust
Plot Model-Based Clustering Results
mclustDAtrain
MclustDA Training
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.
grid1
Generate grid points
emE
EM algorithm starting with E-step for a parameterized MVN mixture model.
mvn
Multivariate Normal Fit
mclust2Dplot
Plot two-dimensional data modelled by an MVN mixture.
hclass
Classifications from Hierarchical Agglomeration
uncerPlot
Uncertainty Plot for Model-Based Clustering
hcE
Model-based Hierarchical Clustering
summary.EMclust
Summary function for EMclust
bicEMtrain
Select models in discriminant analysis using BIC
partconv
Convert partitioning into numerical vector.
mclust-internal
Internal MCLUST functions
cdens
Component Density for Parameterized MVN Mixture Models
mapClass
Correspondence between classifications.
diabetes
Diabetes data
lansing
Maple trees in Lansing Woods
chevron
Simulated minefield data