MclustDA discriminant analysis
Subset selection for GMMDR directions based on BIC.
Acidity data
Simulated minefield data
Pairwise Scatter Plots showing Classification
Classification error
Combining Matrix
Model-Based Clustering
Combining Gaussian Mixture Components for Clustering
Resampling-based Inference for Gaussian finite mixture models
Internal clustCombi functions
Default conjugate prior for Gaussian mixtures.
Plot Classifications Corresponding to Successive Combined Solutions
Set control values for use with the EM algorithm.
Optimal number of clusters obtained by combining mixture components
MclustDA cross-validation
Convert mixture component covariances to matrix form.
EM algorithm starting with E-step for a parameterized Gaussian mixture model.
Density Estimation via Model-Based Clustering
ICL for an estimated Gaussian Mixture Model
Identifying Connected Components in Gaussian Finite Mixture Models for Clustering
Density for Parameterized MVN Mixtures
Missing data imputation via the mix package
Plot Entropy Plots
Plot one-dimensional data modeled by an MVN mixture.
Diagnostic plots for mclustDensity estimation
Draw error bars on a plot
Highest Density Region (HDR) Levels
Majority vote
Log-Likelihood of a MclustDA object
Plot two-dimensional data modelled by an MVN mixture.
Model-based Hierarchical Clustering
Adjusted Rand Index
EM algorithm starting with M-step for parameterized MVN mixture models.
EM algorithm with weights starting with M-step for parameterized MVN mixture models
BIC for Model-Based Clustering
Classifies Data According to Unique Observations
Plot Model-Based Clustering Results
Swiss banknotes data
Update BIC values for parameterized Gaussian mixture models
Classify multivariate observations by Gaussian finite mixture modeling
Plot of bootstrap distributions for mixture model parameters
Component Density for a Parameterized MVN Mixture Model
Aproximate Hypervolume for Multivariate Data
Number of Variance Parameters in Gaussian Mixture Models
Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modeling
Density estimate of multivariate observations by Gaussian finite mixture modeling
Plotting method for MclustDA discriminant analysis
Conjugate Prior for Gaussian Mixtures.
Convert mixture component covariances to decomposition form.
Numeric Encoding of a Partitioning
Simulate from Parameterized MVN Mixture Models
Cumulative Distribution and Quantiles for a univariate Gaussian mixture
distribution
Plotting method for dimension reduction for model-based clustering and classification
Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Default values for use with MCLUST package
Plot Combined Clusterings Results
Density or uncertainty surface for bivariate mixtures
Thyroid gland data
Weighted means, covariance and scattering matrices conditioning on a weighted matrix.
Simulate from a Parameterized MVN Mixture Model
Summarizing Gaussian Finite Mixture Model Fits
Bootstrap Likelihood Ratio Test for the Number of Mixture Components
Simulated Cross Data
E-step for parameterized Gaussian mixture models.
ICL Criterion for Model-Based Clustering
Data Simulated from a 14-Component Mixture
EM algorithm starting with M-step for a parameterized Gaussian mixture model.
E-step in the EM algorithm for a parameterized Gaussian mixture model.
M-step for parameterized Gaussian mixture models.
Baudry_etal_2010_JCGS_examples
Simulated Example Datasets From Baudry et al. (2010)
BIC for Parameterized Gaussian Mixture Models
Component Density for Parameterized MVN Mixture Models
Coordinate projections of multidimensional data modeled by an MVN mixture.
Diabetes data
GvHD Dataset
Tree structure obtained from combining mixture components
ICL Plot for Model-Based Clustering
Cluster multivariate observations by Gaussian finite mixture modeling
Model-based Hierarchical Clustering
Log-Likelihood of a Mclust object
Pairwise Scatter Plots showing Missing Data Imputations
EM algorithm starting with E-step for parameterized Gaussian mixture models.
Summary Function for Bootstrap Inference for Gaussian Finite Mixture Models
Deprecated Functions in mclust package
Summarizing discriminant analysis based on Gaussian finite mixture modeling.
Classifications from Hierarchical Agglomeration
Classification given Probabilities
Internal MCLUST functions
MCLUST Model Names
Template for variance specification for parameterized Gaussian mixture models
Number of Estimated Parameters in Gaussian Mixture Models
Correspondence between classifications.
Log-likelihood from a table of BIC values for parameterized Gaussian mixture models
Best model based on BIC
Univariate or Multivariate Normal Fit
M-step for a parameterized Gaussian mixture model.
Univariate or Multivariate Normal Fit
Plots for Mixture-Based Density Estimate
BIC Plot for Model-Based Clustering
Random projections of multidimensional data modeled by an MVN mixture.
Random hierarchical structure
Indicator Variables given Classification
Uncertainty Plot for Model-Based Clustering
Summarizing dimension reduction method for model-based clustering and classification
Summary function for model-based clustering via BIC
Dimension reduction for model-based clustering and classification