Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Adjusted Rand Index
BIC for Parameterized Gaussian Mixture Models
Brier score to assess the accuracy of probabilistic predictions
Component Density for Parameterized MVN Mixture Models
Component Density for a Parameterized MVN Mixture Model
Cumulative Distribution and Quantiles for a univariate Gaussian mixtur...
Classification error
Estimation of class prior probabilities by EM algorithm
Pairwise Scatter Plots showing Classification
Internal clustCombi functions
Combining Gaussian Mixture Components for Clustering
Optimal number of clusters obtained by combining mixture components
Plot Classifications Corresponding to Successive Combined Solutions
Tree structure obtained from combining mixture components
Combining Matrix
Coordinate projections of multidimensional data modeled by an MVN mixt...
Weighted means, covariance and scattering matrices conditioning on a w...
Discriminant coordinates data projection
MclustDA cross-validation
Convert mixture component covariances to matrix form
Default conjugate prior for Gaussian mixtures
Density for Parameterized MVN Mixtures
Diagnostic plots for mclustDensity estimation
Density Estimation via Model-Based Clustering
Density of multivariate Gaussian distribution
Partition the data by grouping together duplicated data
EM algorithm starting with E-step for parameterized Gaussian mixture m...
Set control values for use with the EM algorithm
EM algorithm starting with E-step for a parameterized Gaussian mixture...
Plot Entropy Plots
Draw error bars on a plot
E-step for parameterized Gaussian mixture models.
E-step in the EM algorithm for a parameterized Gaussian mixture model.
Identifying Connected Components in Gaussian Finite Mixture Models for...
Model-based Agglomerative Hierarchical Clustering
Model-based Hierarchical Clustering
Classifications from Hierarchical Agglomeration
Random hierarchical structure
Highest Density Region (HDR) Levels
Aproximate Hypervolume for Multivariate Data
ICL for an estimated Gaussian Mixture Model
Missing data imputation via the mix package
Pairwise Scatter Plots showing Missing Data Imputations
Log-Likelihood of a Mclust object
Log-Likelihood of a MclustDA object
Log sum of exponentials
Majority vote
Classification given Probabilities
Correspondence between classifications
Deprecated Functions in mclust package
Internal MCLUST functions
Gaussian Mixture Modelling for Model-Based Clustering, Classification,...
Default values for use with MCLUST package
Model-Based Clustering
Plot one-dimensional data modeled by an MVN mixture.
Plot two-dimensional data modelled by an MVN mixture
BIC for Model-Based Clustering
Update BIC values for parameterized Gaussian mixture models
Resampling-based Inference for Gaussian finite mixture models
Bootstrap Likelihood Ratio Test for the Number of Mixture Components
MclustDA discriminant analysis
Dimension reduction for model-based clustering and classification
Subset selection for GMMDR directions based on BIC
ICL Criterion for Model-Based Clustering
Log-likelihood from a table of BIC values for parameterized Gaussian m...
Best model based on BIC
MCLUST Model Names
MclustSSC semi-supervised classification
Template for variance specification for parameterized Gaussian mixture...
EM algorithm starting with M-step for parameterized MVN mixture models
EM algorithm with weights starting with M-step for parameterized Gauss...
EM algorithm starting with M-step for a parameterized Gaussian mixture...
M-step for parameterized Gaussian mixture models
M-step for a parameterized Gaussian mixture model
Univariate or Multivariate Normal Fit
Univariate or Multivariate Normal Fit
Number of Estimated Parameters in Gaussian Mixture Models
Number of Variance Parameters in Gaussian Mixture Models
Numeric Encoding of a Partitioning
Classifies Data According to Unique Observations
Plot Combined Clusterings Results
Plots for Mixture-Based Density Estimate
Dendrograms for Model-based Agglomerative Hierarchical Clustering
Plotting method for Mclust model-based clustering
BIC Plot for Model-Based Clustering
Plot of bootstrap distributions for mixture model parameters
Plotting method for MclustDA discriminant analysis
Plotting method for dimension reduction for model-based clustering and...
ICL Plot for Model-Based Clustering
Plotting method for MclustSSC semi-supervised classification
Density estimate of multivariate observations by Gaussian finite mixtu...
Cluster multivariate observations by Gaussian finite mixture modeling
Classify multivariate observations by Gaussian finite mixture modeling
Classify multivariate observations on a dimension reduced subspace by ...
Classification of multivariate observations by semi-supervised Gaussia...
Conjugate Prior for Gaussian Mixtures.
Random orthogonal matrix
Random projections of multidimensional data modeled by an MVN mixture
Convert mixture component covariances to decomposition form.
Simulate from Parameterized MVN Mixture Models
Simulate from a Parameterized MVN Mixture Model
Softmax function
Summarizing Gaussian Finite Mixture Model Fits
Summary function for model-based clustering via BIC
Summary Function for Bootstrap Inference for Gaussian Finite Mixture M...
Summarizing discriminant analysis based on Gaussian finite mixture mod...
Summarizing dimension reduction method for model-based clustering and ...
Summarizing semi-supervised classification model based on Gaussian fin...
Density or uncertainty surface for bivariate mixtures
Uncertainty Plot for Model-Based Clustering
Indicator Variables given Classification
Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.