Man pages for Keefe-Murphy/MoEClust
Parsimonious Model-Based Clustering with Covariates

aisAustralian Institute of Sport data
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_aitkenAitken Acceleration
MoE_clustMoEClust: Parsimonious Model-Based Clustering with Covariates
MoEClustMoEClust: Parsimonious Model-Based Clustering with Covariates
MoE_compareChoose the best MoEClust model
MoE_controlSet control values for use with MoEClust
MoE_critMoEClust BIC, ICL, and AIC Model-Selection Criteria
MoE_densDensity for MoEClust Mixture Models
MoE_estepCompute the Responsility Matrix and Log-likelihood for...
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_qclassQuantile-Based Clustering for Univariate Data
MoE_UncertaintyPlot Clustering Uncertainties
noise_volApproximate Hypervolume Estimate
plot.MoEClustPlot MoEClust Results
predict.MoEClustPredictions for MoEClust models
Keefe-Murphy/MoEClust documentation built on March 22, 2018, 2:42 p.m.