Man pages for MoEClust
Gaussian Parsimonious Clustering Models with Covariates

aisAustralian Institute of Sport data
aitkenAitken Acceleration
as.MclustConvert MoEClust objects to the Mclust class
CO2dataGNP and CO2 Data Set
drop_constantsDrop constant variables from a formula
drop_levelsDrop unused factor levels to predict from unseen data
expert_covarAccount for extra variability in covariance matrices with...
force_posiDiagForce diagonal elements of a triangular matrix to be positive
MoE_clustMoEClust: Gaussian Parsimonious Clustering Models with...
MoEClust-packageMoEClust: Gaussian Parsimonious Clustering Models with...
MoE_compareChoose the best MoEClust model
MoE_controlSet control values for use with MoEClust
MoE_critMoEClust BIC, ICL, and AIC Model-Selection Criteria
MoE_cstepC-step for MoEClust Models
MoE_densDensity for MoEClust Mixture Models
MoE_estepE-step for MoEClust Models
MoE_gpairsGeneralised Pairs Plots for MoEClust Mixture Models
MoE_mahalaMahalanobis Distance Outlier Detection for Multivariate...
MoE_newsShow the NEWS file
MoE_plotCritModel Selection Criteria Plot for MoEClust Mixture Models
MoE_plotGatePlot MoEClust Gating Network
MoE_plotLogLikPlot the Log-Likelihood of a MoEClust Mixture Model
MoE_UncertaintyPlot Clustering Uncertainties
noise_volApproximate Hypervolume Estimate
plot.MoEClustPlot MoEClust Results
predict.MoEClustPredictions for MoEClust models
quant_clustQuantile-Based Clustering for Univariate Data
MoEClust documentation built on Dec. 11, 2018, 5:05 p.m.