Baudry_etal_2010_JCGS_examples Simulated Example Datasets From Baudry et al. (2010) BrierScore Brier score to assess the accuracy of probabilistic predictions EuroUnemployment Unemployment data for European countries in 2014 GvHD GvHD Dataset Mclust Model-Based Clustering MclustBootstrap Resampling-based Inference for Gaussian finite mixture models MclustDA MclustDA discriminant analysis MclustDR Dimension reduction for model-based clustering and classification MclustDRsubsel Subset selection for GMMDR directions based on BIC MclustSSC MclustSSC semi-supervised classification acidity Acidity data adjustedRandIndex Adjusted Rand Index banknote Swiss banknotes data bic BIC for Parameterized Gaussian Mixture Models cdens Component Density for Parameterized MVN Mixture Models cdensE Component Density for a Parameterized MVN Mixture Model cdfMclust Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution chevron Simulated minefield data clPairs Pairwise Scatter Plots showing Classification classError Classification error classPriorProbs Estimation of class prior probabilities by EM algorithm clustCombi Combining Gaussian Mixture Components for Clustering clustCombiOptim Optimal number of clusters obtained by combining mixture components combMat Combining Matrix combiPlot Plot Classifications Corresponding to Successive Combined Solutions combiTree Tree structure obtained from combining mixture components 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 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 emControl Set control values for use with the EM algorithm emE 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. gmmhd Identifying Connected Components in Gaussian Finite Mixture Models for Clustering hc Model-based Agglomerative Hierarchical Clustering hcE Model-based Hierarchical Clustering hcRandomPairs Random hierarchical structure hclass Classifications from Hierarchical Agglomeration 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 mclust-package 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 mclustBootstrapLRT Bootstrap Likelihood Ratio Test for the Number of Mixture Components 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 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 mstep M-step for parameterized Gaussian mixture models mstepE M-step for a parameterized Gaussian mixture model mvn Univariate or Multivariate Normal Fit mvnX 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.Mclust Plotting method for Mclust model-based clustering plot.MclustBootstrap Plot of bootstrap distributions for mixture model parameters plot.MclustDA Plotting method for MclustDA discriminant analysis plot.MclustDR Plotting method for dimension reduction for model-based clustering and classification plot.MclustSSC Plotting method for MclustSSC semi-supervised classification plot.clustCombi Plot Combined Clusterings Results plot.densityMclust Plots for Mixture-Based Density Estimate plot.hc Dendrograms for Model-based Agglomerative Hierarchical Clustering plot.mclustBIC BIC Plot for Model-Based Clustering plot.mclustICL ICL Plot for Model-Based Clustering 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 predict.densityMclust Density estimate of multivariate observations by Gaussian finite mixture modeling priorControl Conjugate Prior for Gaussian Mixtures. randProj Random projections of multidimensional data modeled by an MVN mixture randomOrthogonalMatrix Random orthogonal matrix sigma2decomp Convert mixture component covariances to decomposition form. sim Simulate from Parameterized MVN Mixture Models simE Simulate from a Parameterized MVN Mixture Model softmax Softmax function summary.Mclust Summarizing Gaussian Finite Mixture Model Fits 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.MclustSSC Summarizing semi-supervised classification model based on Gaussian finite mixtures summary.mclustBIC Summary function for model-based clustering via BIC surfacePlot Density or uncertainty surface for bivariate mixtures 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