A B C D E G H I L M N P Q R S T U W
mclust-package | Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation |
acidity | Acidity data |
adjustedRandIndex | Adjusted Rand Index |
as.hclust.hc | Model-based Agglomerative Hierarchical Clustering |
banknote | Swiss banknotes data |
Baudry_etal_2010_JCGS_examples | Simulated Example Datasets From Baudry et al. (2010) |
bic | BIC for Parameterized Gaussian Mixture Models |
bicEMtrain | Deprecated Functions in mclust package |
BrierScore | Brier score to assess the accuracy of probabilistic predictions |
cdens | Component Density for Parameterized MVN Mixture Models |
cdensE | Component Density for a Parameterized MVN Mixture Model |
cdensEEE | Component Density for a Parameterized MVN Mixture Model |
cdensEEI | Component Density for a Parameterized MVN Mixture Model |
cdensEEV | Component Density for a Parameterized MVN Mixture Model |
cdensEII | Component Density for a Parameterized MVN Mixture Model |
cdensEVE | Component Density for a Parameterized MVN Mixture Model |
cdensEVI | Component Density for a Parameterized MVN Mixture Model |
cdensEVV | Component Density for a Parameterized MVN Mixture Model |
cdensV | Component Density for a Parameterized MVN Mixture Model |
cdensVEE | Component Density for a Parameterized MVN Mixture Model |
cdensVEI | Component Density for a Parameterized MVN Mixture Model |
cdensVEV | Component Density for a Parameterized MVN Mixture Model |
cdensVII | Component Density for a Parameterized MVN Mixture Model |
cdensVVE | Component Density for a Parameterized MVN Mixture Model |
cdensVVI | Component Density for a Parameterized MVN Mixture Model |
cdensVVV | Component Density for a Parameterized MVN Mixture Model |
cdensX | Component Density for a Parameterized MVN Mixture Model |
cdensXII | Component Density for a Parameterized MVN Mixture Model |
cdensXXI | Component Density for a Parameterized MVN Mixture Model |
cdensXXX | Component Density for a Parameterized MVN Mixture Model |
cdfMclust | Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution |
chevron | Simulated minefield data |
classError | Classification error |
classPriorProbs | Estimation of class prior probabilities by EM algorithm |
clPairs | Pairwise Scatter Plots showing Classification |
clPairsLegend | Pairwise Scatter Plots showing Classification |
clustCombi | Combining Gaussian Mixture Components for Clustering |
clustCombiOptim | Optimal number of clusters obtained by combining mixture components |
combiPlot | Plot Classifications Corresponding to Successive Combined Solutions |
combiTree | Tree structure obtained from combining mixture components |
combMat | Combining Matrix |
coordProj | Coordinate projections of multidimensional data modeled by an MVN mixture. |
covw | Weighted means, covariance and scattering matrices conditioning on a weighted matrix |
crimcoords | Discriminant coordinates data projection |
cross | Simulated Cross Data |
cv.MclustDA | Deprecated Functions in mclust package |
cv1EMtrain | Deprecated Functions in mclust package |
cvMclustDA | MclustDA cross-validation |
decomp2sigma | Convert mixture component covariances to matrix form |
defaultPrior | Default conjugate prior for Gaussian mixtures |
dens | Density for Parameterized MVN Mixtures |
densityMclust | Density Estimation via Model-Based Clustering |
densityMclust.diagnostic | Diagnostic plots for 'mclustDensity' estimation |
diabetes | Diabetes Data (flawed) |
dmvnorm | Density of multivariate Gaussian distribution |
dupPartition | Partition the data by grouping together duplicated data |
em | EM algorithm starting with E-step for parameterized Gaussian mixture models |
EMclust | BIC for Model-Based Clustering |
emControl | Set control values for use with the EM algorithm |
emE | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEEE | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEEI | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEEV | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEII | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEVE | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEVI | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emEVV | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emV | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVEE | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVEI | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVEV | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVII | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVVE | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVVI | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emVVV | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emX | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emXII | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emXXI | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
emXXX | EM algorithm starting with E-step for a parameterized Gaussian mixture model |
entPlot | Plot Entropy Plots |
errorBars | Draw error bars on a plot |
estep | E-step for parameterized Gaussian mixture models. |
estepE | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEE | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEI | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEEV | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEII | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEVE | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEVI | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepEVV | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepV | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVEE | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVEI | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVEV | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVII | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVVE | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVVI | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
estepVVV | E-step in the EM algorithm for a parameterized Gaussian mixture model. |
EuroUnemployment | Unemployment data for European countries in 2014 |
ex4.1 | Simulated Example Datasets From Baudry et al. (2010) |
ex4.2 | Simulated Example Datasets From Baudry et al. (2010) |
ex4.3 | Simulated Example Datasets From Baudry et al. (2010) |
ex4.4.1 | Simulated Example Datasets From Baudry et al. (2010) |
ex4.4.2 | Simulated Example Datasets From Baudry et al. (2010) |
gmmhd | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
gmmhdClassify | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
gmmhdClusterCores | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
GvHD | GvHD Dataset |
GvHD.control | GvHD Dataset |
GvHD.pos | GvHD Dataset |
hc | Model-based Agglomerative Hierarchical Clustering |
hcE | Model-based Hierarchical Clustering |
hcEEE | Model-based Hierarchical Clustering |
hcEII | Model-based Hierarchical Clustering |
hclass | Classifications from Hierarchical Agglomeration |
hcRandomPairs | Random hierarchical structure |
hcV | Model-based Hierarchical Clustering |
hcVII | Model-based Hierarchical Clustering |
hcVVV | Model-based Hierarchical Clustering |
hdrlevels | Highest Density Region (HDR) Levels |
hypvol | Aproximate Hypervolume for Multivariate Data |
icl | ICL for an estimated Gaussian Mixture Model |
imputeData | Missing data imputation via the 'mix' package |
imputePairs | Pairwise Scatter Plots showing Missing Data Imputations |
logLik.Mclust | Log-Likelihood of a 'Mclust' object |
logLik.MclustDA | Log-Likelihood of a 'MclustDA' object |
logsumexp | Log sum of exponentials |
majorityVote | Majority vote |
map | Classification given Probabilities |
mapClass | Correspondence between classifications |
matchCluster | Missing data imputation via the 'mix' package |
Mclust | Model-Based Clustering |
mclust | Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation |
mclust.options | Default values for use with MCLUST package |
mclust1Dplot | Plot one-dimensional data modeled by an MVN mixture. |
mclust2Dplot | Plot two-dimensional data modelled by an MVN mixture |
mclustBIC | BIC for Model-Based Clustering |
mclustBICupdate | Update BIC values for parameterized Gaussian mixture models |
MclustBootstrap | Resampling-based Inference for Gaussian finite mixture models |
mclustBootstrapLRT | Bootstrap Likelihood Ratio Test for the Number of Mixture Components |
MclustDA | MclustDA discriminant analysis |
MclustDR | Dimension reduction for model-based clustering and classification |
MclustDRrecoverdir | Subset selection for GMMDR directions based on BIC |
MclustDRsubsel | Subset selection for GMMDR directions based on BIC |
MclustDRsubsel1cycle | Subset selection for GMMDR directions based on BIC |
MclustDRsubsel_classif | Subset selection for GMMDR directions based on BIC |
MclustDRsubsel_cluster | Subset selection for GMMDR directions based on BIC |
mclustICL | ICL Criterion for Model-Based Clustering |
mclustLoglik | Log-likelihood from a table of BIC values for parameterized Gaussian mixture models |
mclustModel | Best model based on BIC |
mclustModelNames | MCLUST Model Names |
MclustSSC | MclustSSC semi-supervised classification |
mclustVariance | Template for variance specification for parameterized Gaussian mixture models |
me | EM algorithm starting with M-step for parameterized MVN 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 |
meEEE | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEEI | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEEV | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEII | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEVE | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEVI | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meEVV | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meV | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVEE | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVEI | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVEV | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVII | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVVE | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVVI | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meVVV | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meX | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meXII | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meXXI | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
meXXX | EM algorithm starting with M-step for a parameterized Gaussian mixture model |
mstep | M-step for parameterized Gaussian mixture models |
mstepE | M-step for a parameterized Gaussian mixture model |
mstepEEE | M-step for a parameterized Gaussian mixture model |
mstepEEI | M-step for a parameterized Gaussian mixture model |
mstepEEV | M-step for a parameterized Gaussian mixture model |
mstepEII | M-step for a parameterized Gaussian mixture model |
mstepEVE | M-step for a parameterized Gaussian mixture model |
mstepEVI | M-step for a parameterized Gaussian mixture model |
mstepEVV | M-step for a parameterized Gaussian mixture model |
mstepV | M-step for a parameterized Gaussian mixture model |
mstepVEE | M-step for a parameterized Gaussian mixture model |
mstepVEI | M-step for a parameterized Gaussian mixture model |
mstepVEV | M-step for a parameterized Gaussian mixture model |
mstepVII | M-step for a parameterized Gaussian mixture model |
mstepVVE | M-step for a parameterized Gaussian mixture model |
mstepVVI | M-step for a parameterized Gaussian mixture model |
mstepVVV | M-step for a parameterized Gaussian mixture model |
mvn | Univariate or Multivariate Normal Fit |
mvnX | Univariate or Multivariate Normal Fit |
mvnXII | Univariate or Multivariate Normal Fit |
mvnXXI | Univariate or Multivariate Normal Fit |
mvnXXX | Univariate or Multivariate Normal Fit |
nMclustParams | Number of Estimated Parameters in Gaussian Mixture Models |
nVarParams | Number of Variance Parameters in Gaussian Mixture Models |
partconv | Numeric Encoding of a Partitioning |
partuniq | Classifies Data According to Unique Observations |
plot.clustCombi | Plot Combined Clusterings Results |
plot.crimcoords | Discriminant coordinates data projection |
plot.densityMclust | Plots for Mixture-Based Density Estimate |
plot.gmmhd | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
plot.hc | Dendrograms for Model-based Agglomerative Hierarchical Clustering |
plot.Mclust | Plotting method for Mclust model-based clustering |
plot.mclustBIC | BIC Plot for Model-Based Clustering |
plot.MclustBootstrap | Plot of bootstrap distributions for mixture model parameters |
plot.mclustBootstrapLRT | Bootstrap Likelihood Ratio Test for the Number of Mixture Components |
plot.MclustDA | Plotting method for MclustDA discriminant analysis |
plot.MclustDR | Plotting method for dimension reduction for model-based clustering and classification |
plot.mclustICL | ICL Plot for Model-Based Clustering |
plot.MclustSSC | Plotting method for MclustSSC semi-supervised classification |
plotDensityMclust1 | Plots for Mixture-Based Density Estimate |
plotDensityMclust2 | Plots for Mixture-Based Density Estimate |
plotDensityMclustd | Plots for Mixture-Based Density Estimate |
plotEvalues.MclustDR | Plotting method for dimension reduction for model-based clustering and classification |
predict.densityMclust | Density estimate of multivariate observations by Gaussian finite mixture modeling |
predict.Mclust | Cluster multivariate observations by Gaussian finite mixture modeling |
predict.MclustDA | Classify multivariate observations by Gaussian finite mixture modeling |
predict.MclustDR | Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling |
predict.MclustSSC | Classification of multivariate observations by semi-supervised Gaussian finite mixtures |
predict2D.MclustDR | Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling |
print.clustCombi | Combining Gaussian Mixture Components for Clustering |
print.crimcoords | Discriminant coordinates data projection |
print.gmmhd | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
print.hc | Model-based Agglomerative Hierarchical Clustering |
print.Mclust | Model-Based Clustering |
print.mclustBIC | BIC for Model-Based Clustering |
print.MclustBootstrap | Resampling-based Inference for Gaussian finite mixture models |
print.mclustBootstrapLRT | Bootstrap Likelihood Ratio Test for the Number of Mixture Components |
print.MclustDA | MclustDA discriminant analysis |
print.MclustDR | Dimension reduction for model-based clustering and classification |
print.MclustDRsubsel | Subset selection for GMMDR directions based on BIC |
print.mclustICL | ICL Criterion for Model-Based Clustering |
print.mclustLoglik | Log-likelihood from a table of BIC values for parameterized Gaussian mixture models |
print.MclustSSC | MclustSSC semi-supervised classification |
print.summary.clustCombi | Combining Gaussian Mixture Components for Clustering |
print.summary.crimcoords | Discriminant coordinates data projection |
print.summary.gmmhd | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
print.summary.Mclust | Summarizing Gaussian Finite Mixture Model Fits |
print.summary.mclustBIC | Summary function for model-based clustering via BIC |
print.summary.MclustBootstrap | Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models |
print.summary.MclustDA | Summarizing discriminant analysis based on Gaussian finite mixture modeling |
print.summary.MclustDR | Summarizing dimension reduction method for model-based clustering and classification |
print.summary.mclustICL | ICL Criterion for Model-Based Clustering |
print.summary.MclustSSC | Summarizing semi-supervised classification model based on Gaussian finite mixtures |
printSummaryMclustBIC | Summary function for model-based clustering via BIC |
printSummaryMclustBICn | Summary function for model-based clustering via BIC |
priorControl | Conjugate Prior for Gaussian Mixtures. |
quantileMclust | Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution |
randomOrthogonalMatrix | Random orthogonal matrix |
randomPairs | Random hierarchical structure |
randProj | Random projections of multidimensional data modeled by an MVN mixture |
sigma2decomp | Convert mixture component covariances to decomposition form. |
sim | Simulate from Parameterized MVN Mixture Models |
simE | Simulate from a Parameterized MVN Mixture Model |
simEEE | Simulate from a Parameterized MVN Mixture Model |
simEEI | Simulate from a Parameterized MVN Mixture Model |
simEEV | Simulate from a Parameterized MVN Mixture Model |
simEII | Simulate from a Parameterized MVN Mixture Model |
simEVE | Simulate from a Parameterized MVN Mixture Model |
simEVI | Simulate from a Parameterized MVN Mixture Model |
simEVV | Simulate from a Parameterized MVN Mixture Model |
simV | Simulate from a Parameterized MVN Mixture Model |
simVEE | Simulate from a Parameterized MVN Mixture Model |
simVEI | Simulate from a Parameterized MVN Mixture Model |
simVEV | Simulate from a Parameterized MVN Mixture Model |
simVII | Simulate from a Parameterized MVN Mixture Model |
simVVE | Simulate from a Parameterized MVN Mixture Model |
simVVI | Simulate from a Parameterized MVN Mixture Model |
simVVV | Simulate from a Parameterized MVN Mixture Model |
softmax | Softmax function |
summary.clustCombi | Combining Gaussian Mixture Components for Clustering |
summary.crimcoords | Discriminant coordinates data projection |
summary.gmmhd | Identifying Connected Components in Gaussian Finite Mixture Models for Clustering |
summary.Mclust | Summarizing Gaussian Finite Mixture Model Fits |
summary.mclustBIC | Summary function for model-based clustering via BIC |
summary.MclustBootstrap | Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models |
summary.MclustDA | Summarizing discriminant analysis based on Gaussian finite mixture modeling |
summary.MclustDR | Summarizing dimension reduction method for model-based clustering and classification |
summary.MclustDRsubsel | Subset selection for GMMDR directions based on BIC |
summary.mclustICL | ICL Criterion for Model-Based Clustering |
summary.MclustSSC | Summarizing semi-supervised classification model based on Gaussian finite mixtures |
summaryMclustBIC | Summary function for model-based clustering via BIC |
summaryMclustBICn | Summary function for model-based clustering via BIC |
surfacePlot | Density or uncertainty surface for bivariate mixtures |
Test1D | Simulated Example Datasets From Baudry et al. (2010) |
thyroid | UCI Thyroid Gland Data |
uncerPlot | Uncertainty Plot for Model-Based Clustering |
unmap | Indicator Variables given Classification |
wdbc | UCI Wisconsin Diagnostic Breast Cancer Data |
wreath | Data Simulated from a 14-Component Mixture |