| acidity | Acidity data |
| adjustedRandIndex | Adjusted Rand Index |
| banknote | Swiss banknotes data |
| Baudry_etal_2010_JCGS_examples | Simulated Example Datasets From Baudry et al. (2010) |
| bic | BIC for Parameterized Gaussian Mixture Models |
| BrierScore | Brier score to assess the accuracy of probabilistic... |
| 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... |
| chevron | Simulated minefield data |
| classError | Classification error |
| classPriorProbs | Estimation of class prior probabilities by EM algorithm |
| clPairs | Pairwise Scatter Plots showing Classification |
| clustCombi | Combining Gaussian Mixture Components for Clustering |
| clustCombi-internals | Internal clustCombi functions |
| clustCombiOptim | Optimal number of clusters obtained by combining mixture... |
| combiPlot | Plot Classifications Corresponding to Successive Combined... |
| combiTree | Tree structure obtained from combining mixture components |
| combMat | Combining Matrix |
| coordProj | Coordinate projections of multidimensional data modeled by an... |
| covw | Weighted means, covariance and scattering matrices... |
| crimcoords | Discriminant coordinates data projection |
| cross | Simulated Cross Data |
| 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... |
| emControl | Set control values for use with the EM algorithm |
| emE | EM algorithm starting with E-step for a parameterized... |
| 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... |
| EuroUnemployment | Unemployment data for European countries in 2014 |
| gmmhd | Identifying Connected Components in Gaussian Finite Mixture... |
| GvHD | GvHD Dataset |
| hc | Model-based Agglomerative Hierarchical Clustering |
| hcE | Model-based Hierarchical Clustering |
| hclass | Classifications from Hierarchical Agglomeration |
| hcRandomPairs | Random hierarchical structure |
| 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 | Model-Based Clustering |
| 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... |
| MclustDA | MclustDA discriminant analysis |
| mclust-deprecated | Deprecated Functions in mclust package |
| MclustDR | Dimension reduction for model-based clustering and... |
| MclustDRsubsel | Subset selection for GMMDR directions based on BIC |
| mclustICL | ICL Criterion for Model-Based Clustering |
| mclust-internal | Internal MCLUST functions |
| mclustLoglik | Log-likelihood from a table of BIC values for parameterized... |
| mclustModel | Best model based on BIC |
| mclustModelNames | MCLUST Model Names |
| mclust.options | Default values for use with MCLUST package |
| mclust-package | Gaussian Mixture Modelling for Model-Based Clustering,... |
| MclustSSC | MclustSSC semi-supervised classification |
| mclustVariance | Template for variance specification for parameterized... |
| me | EM algorithm starting with M-step for parameterized MVN... |
| meE | EM algorithm starting with M-step for a parameterized... |
| me.weighted | EM algorithm with weights starting with M-step for... |
| 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.clustCombi | Plot Combined Clusterings Results |
| plot.densityMclust | Plots for Mixture-Based Density Estimate |
| plot.hc | Dendrograms for Model-based Agglomerative Hierarchical... |
| plot.Mclust | Plotting method for Mclust model-based clustering |
| plot.mclustBIC | BIC Plot for Model-Based Clustering |
| plot.MclustBoostrap | 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... |
| plot.mclustICL | ICL Plot for Model-Based Clustering |
| plot.MclustSSC | Plotting method for MclustSSC semi-supervised classification |
| predict.densityMclust | Density estimate of multivariate observations by Gaussian... |
| predict.Mclust | Cluster multivariate observations by Gaussian finite mixture... |
| predict.MclustDA | Classify multivariate observations by Gaussian finite mixture... |
| predict.MclustDR | Classify multivariate observations on a dimension reduced... |
| predict.MclustSSC | Classification of multivariate observations by... |
| priorControl | Conjugate Prior for Gaussian Mixtures. |
| randomOrthogonalMatrix | Random orthogonal matrix |
| randProj | Random projections of multidimensional data modeled by an MVN... |
| 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.mclustBIC | Summary function for model-based clustering via BIC |
| summary.MclustBootstrap | Summary Function for Bootstrap Inference for Gaussian Finite... |
| summary.MclustDA | Summarizing discriminant analysis based on Gaussian finite... |
| summary.MclustDR | Summarizing dimension reduction method for model-based... |
| summary.MclustSSC | Summarizing semi-supervised classification model based on... |
| 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 |
