`install.packages('mclust')`

58,836

6.1

GPL (>= 2)

February 23rd, 2024

acidity

Acidity data

cdens

Component Density for Parameterized MVN Mixture Models

clPairs

Pairwise Scatter Plots showing Classification

adjustedRandIndex

Adjusted Rand Index

banknote

Swiss banknotes data

chevron

Simulated minefield data

bic

BIC for Parameterized Gaussian Mixture Models

cdensE

Component Density for a Parameterized MVN Mixture Model

covw

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

classError

Classification error

cdfMclust

Cumulative Distribution and Quantiles for a univariate Gaussian mixture
distribution

crimcoords

Discriminant coordinates data projection

clustCombiOptim

Optimal number of clusters obtained by combining mixture components

clustCombi

Combining Gaussian Mixture Components for Clustering

dens

Density for Parameterized MVN Mixtures

coordProj

Coordinate projections of multidimensional data modeled by an MVN mixture.

defaultPrior

Default conjugate prior for Gaussian mixtures

cvMclustDA

MclustDA cross-validation

errorBars

Draw error bars on a plot

densityMclust.diagnostic

Diagnostic plots for

`mclustDensity`

estimationdmvnorm

Density of multivariate Gaussian distribution

cross

Simulated Cross Data

classPriorProbs

Estimation of class prior probabilities by EM algorithm

combMat

Combining Matrix

dupPartition

Partition the data by grouping together duplicated data

densityMclust

Density Estimation via Model-Based Clustering

combiPlot

Plot Classifications Corresponding to Successive Combined Solutions

estep

E-step for parameterized Gaussian mixture models.

em

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

entPlot

Plot Entropy Plots

estepE

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

diabetes

Diabetes Data (flawed)

emE

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

logsumexp

Log sum of exponentials

combiTree

Tree structure obtained from combining mixture components

hdrlevels

Highest Density Region (HDR) Levels

gmmhd

Identifying Connected Components in Gaussian Finite Mixture Models for Clustering

decomp2sigma

Convert mixture component covariances to matrix form

emControl

Set control values for use with the EM algorithm

logLik.MclustDA

Log-Likelihood of a

`MclustDA`

objectclustCombi-internal

Internal clustCombi functions

imputeData

Missing data imputation via the mix package

mclustBIC

BIC for Model-Based Clustering

hypvol

Aproximate Hypervolume for Multivariate Data

icl

ICL for an estimated Gaussian Mixture Model

majorityVote

Majority vote

mapClass

Correspondence between classifications

hcE

Model-based Hierarchical Clustering

hc

Model-based Agglomerative Hierarchical Clustering

map

Classification given Probabilities

mclust2Dplot

Plot two-dimensional data modelled by an MVN mixture

mclust-deprecated

Deprecated Functions in mclust package

mclustICL

ICL Criterion for Model-Based Clustering

mclustLoglik

Log-likelihood from a table of BIC values for parameterized Gaussian mixture models

me.weighted

EM algorithm with weights starting with M-step for parameterized Gaussian mixture models

meE

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

mclust-internal

Internal MCLUST functions

hcRandomPairs

Random hierarchical structure

logLik.Mclust

Log-Likelihood of a

`Mclust`

objectmstepE

M-step for a parameterized Gaussian mixture model

imputePairs

Pairwise Scatter Plots showing Missing Data Imputations

mclust-package

Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

mclust1Dplot

Plot one-dimensional data modeled by an MVN mixture.

mstep

M-step for parameterized Gaussian mixture models

mclustBICupdate

Update BIC values for parameterized Gaussian mixture models

hclass

Classifications from Hierarchical Agglomeration

plot.Mclust

Plotting method for Mclust model-based clustering

mclust.options

Default values for use with MCLUST package

mclustBootstrapLRT

Bootstrap Likelihood Ratio Test for the Number of Mixture Components

mclustVariance

Template for variance specification for parameterized Gaussian mixture models

plot.MclustSSC

Plotting method for MclustSSC semi-supervised classification

plot.mclustBIC

BIC Plot for Model-Based Clustering

plot.MclustBootstrap

Plot of bootstrap distributions for mixture model parameters

partconv

Numeric Encoding of a Partitioning

plot.clustCombi

Plot Combined Clusterings Results

plot.densityMclust

Plots for Mixture-Based Density Estimate

randomOrthogonalMatrix

Random orthogonal matrix

me

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

sim

Simulate from Parameterized MVN Mixture Models

randProj

Random projections of multidimensional data modeled by an MVN mixture

sigma2decomp

Convert mixture component covariances to decomposition form.

plot.hc

Dendrograms for Model-based Agglomerative Hierarchical Clustering

partuniq

Classifies Data According to Unique Observations

mvn

Univariate or Multivariate Normal Fit

predict.MclustDR

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

softmax

Softmax function

summary.MclustDR

Summarizing dimension reduction method for model-based clustering and classification

simE

Simulate from a Parameterized MVN Mixture Model

predict.MclustDA

Classify multivariate observations by Gaussian finite mixture modeling

summary.MclustDA

Summarizing discriminant analysis based on Gaussian finite mixture modeling

plot.MclustDR

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

mvnX

Univariate or Multivariate Normal Fit

predict.MclustSSC

Classification of multivariate observations by semi-supervised Gaussian finite mixtures

predict.Mclust

Cluster multivariate observations by Gaussian finite mixture modeling

plot.MclustDA

Plotting method for MclustDA discriminant analysis

uncerPlot

Uncertainty Plot for Model-Based Clustering

summary.Mclust

Summarizing Gaussian Finite Mixture Model Fits

mclustModel

Best model based on BIC

wdbc

UCI Wisconsin Diagnostic Breast Cancer Data

summary.MclustBootstrap

Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models

mclustModelNames

MCLUST Model Names

nMclustParams

Number of Estimated Parameters in Gaussian Mixture Models

plot.mclustICL

ICL Plot for Model-Based Clustering

summary.MclustSSC

Summarizing semi-supervised classification model based on Gaussian finite mixtures

wreath

Data Simulated from a 14-Component Mixture

unmap

Indicator Variables given Classification

summary.mclustBIC

Summary function for model-based clustering via BIC

nVarParams

Number of Variance Parameters in Gaussian Mixture Models

priorControl

Conjugate Prior for Gaussian Mixtures.

thyroid

UCI Thyroid Gland Data

surfacePlot

Density or uncertainty surface for bivariate mixtures

predict.densityMclust

Density estimate of multivariate observations by Gaussian finite mixture modeling

Baudry_etal_2010_JCGS_examples

Simulated Example Datasets From Baudry et al. (2010)

MclustDA

MclustDA discriminant analysis

MclustDRsubsel

Subset selection for GMMDR directions based on BIC

Mclust

Model-Based Clustering

MclustDR

Dimension reduction for model-based clustering and classification

EuroUnemployment

Unemployment data for European countries in 2014

MclustSSC

MclustSSC semi-supervised classification

BrierScore

Brier score to assess the accuracy of probabilistic predictions

GvHD

GvHD Dataset

MclustBootstrap

Resampling-based Inference for Gaussian finite mixture models