Gaussian Parsimonious Clustering Models with Covariates


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Documentation for package ‘MoEClust’ version 1.2.1

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MoEClust-package MoEClust: Gaussian Parsimonious Clustering Models with Covariates
ais Australian Institute of Sport data
aitken Aitken Acceleration
as.Mclust Convert MoEClust objects to the Mclust class
CO2data GNP and CO2 Data Set
drop_constants Drop constant variables from a formula
drop_levels Drop unused factor levels to predict from unseen data
expert_covar Account for extra variability in covariance matrices with expert covariates
force_posiDiag Force diagonal elements of a triangular matrix to be positive
MoEClust MoEClust: Gaussian Parsimonious Clustering Models with Covariates
MoE_clust MoEClust: Gaussian Parsimonious Clustering Models with Covariates
MoE_compare Choose the best MoEClust model
MoE_control Set control values for use with MoEClust
MoE_crit MoEClust BIC, ICL, and AIC Model-Selection Criteria
MoE_cstep C-step for MoEClust Models
MoE_dens Density for MoEClust Mixture Models
MoE_estep E-step for MoEClust Models
MoE_gpairs Generalised Pairs Plots for MoEClust Mixture Models
MoE_mahala Mahalanobis Distance Outlier Detection for Multivariate Response
MoE_news Show the NEWS file
MoE_plotCrit Model Selection Criteria Plot for MoEClust Mixture Models
MoE_plotGate Plot MoEClust Gating Network
MoE_plotLogLik Plot the Log-Likelihood of a MoEClust Mixture Model
MoE_Uncertainty Plot Clustering Uncertainties
noise_vol Approximate Hypervolume Estimate
plot.MoEClust Plot MoEClust Results
predict.MoEClust Predictions for MoEClust models
print.MoEClust MoEClust: Gaussian Parsimonious Clustering Models with Covariates
print.MoECompare Choose the best MoEClust model
quant_clust Quantile-Based Clustering for Univariate Data
residuals.MoEClust Predictions for MoEClust models
summary.MoEClust MoEClust: Gaussian Parsimonious Clustering Models with Covariates