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mclust (version 3.5)
Model-Based Clustering / Normal Mixture Modeling
Description
Model-based clustering and normal mixture modeling including Bayesian regularization
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Install
install.packages('mclust')
Monthly Downloads
74,509
Version
3.5
License
GPL (>= 2)
Maintainer
Luca Scrucca
Last Published
July 22nd, 2012
Functions in mclust (3.5)
Search all functions
chevron
Simulated minefield data
partuniq
Classifies Data According to Unique Observations
mclustBIC
BIC for Model-Based Clustering
hypvol
Aproximate Hypervolume for Multivariate Data
emE
EM algorithm starting with E-step for a parameterized Gaussian mixture model.
bic
BIC for Parameterized Gaussian Mixture Models
mclustModelNames
MCLUST Model Names
uncerPlot
Uncertainty Plot for Model-Based Clustering
summary.mclustBIC
Summary Function for model-based clustering.
mapClass
Correspondence between classifications.
coordProj
Coordinate projections of multidimensional data modeled by an MVN mixture.
cross
Simulated Cross Data
surfacePlot
Density or uncertainty surface for bivariate mixtures.
plot.mclustDA
Plotting method for MclustDA discriminant analysis.
mclustDA
MclustDA discriminant analysis.
meE
EM algorithm starting with M-step for a parameterized Gaussian mixture model.
cdensE
Component Density for a Parameterized MVN Mixture Model
mclust-internal
Internal MCLUST functions
partconv
Numeric Encoding of a Partitioning
hcE
Model-based Hierarchical Clustering
hclass
Classifications from Hierarchical Agglomeration
densityMclust
Density Estimation via Model-Based Clustering
mclustDAtest
MclustDA Testing
Mclust
Model-Based Clustering
plot.mclustBIC
BIC Plot
sigma2decomp
Convert mixture component covariances to decomposition form.
priorControl
Conjugate Prior for Gaussian Mixtures.
decomp2sigma
Convert mixture component covariances to matrix form.
sim
Simulate from Parameterized MVN Mixture Models
cdens
Component Density for Parameterized MVN Mixture Models
diabetes
Diabetes data
mstepE
M-step for a parameterized Gaussian mixture model.
imputeData
Missing Data Imputation via the mix package
emControl
Set control values for use with the EM algorithm.
nVarParams
Number of Variance Parameters in Gaussian Mixture Models
dens
Density for Parameterized MVN Mixtures
classError
Classification error.
adjustedRandIndex
Adjusted Rand Index
mvnX
Univariate or Multivariate Normal Fit
em
EM algorithm starting with E-step for parameterized Gaussian mixture models.
defaultPrior
Default conjugate prior for Gaussian mixtures.
summary.mclustDAtest
Classification and posterior probability from mclustDAtest.
me
EM algorithm starting with M-step for parameterized MVN mixture models.
clPairs
Pairwise Scatter Plots showing Classification
Defaults.Mclust
List of values controlling defaults for some MCLUST functions.
imputePairs
Pairwise Scatter Plots showing Missing Data Imputations
mclustModel
Best model based on BIC.
mstep
M-step for parameterized Gaussian mixture models.
simE
Simulate from a Parameterized MVN Mixture Model
plot.Mclust
Plot Model-Based Clustering Results
mclust2Dplot
Plot two-dimensional data modelled by an MVN mixture.
mvn
Univariate or Multivariate Normal Fit
hc
Model-based Hierarchical Clustering
wreath
Data Simulated from a 14-Component Mixture
bicEMtrain
Select models in discriminant analysis using BIC
unmap
Indicator Variables given Classification
estepE
E-step in the EM algorithm for a parameterized Gaussian mixture model.
cv1EMtrain
Select discriminant models using cross validation
mclustOptions
Set default values for use with MCLUST.
mclust1Dplot
Plot one-dimensional data modeled by an MVN mixture.
mclustDAtrain
MclustDA Training
plot.densityMclust
Plot Univariate Mclust Density
randProj
Random projections of multidimensional data modeled by an MVN mixture.
summary.mclustModel
Summary Function for MCLUST Models
summary.mclustDAtrain
Models and classifications from mclustDAtrain
map
Classification given Probabilities
estep
E-step for parameterized Gaussian mixture models.
mclustVariance
Template for variance specification for parameterized Gaussian mixture models.
plot.mclustDAtrain
Plot mclustDA training models.