Cluster Analysis with Missing Values by Multiple Imputation

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Documentation for package ‘clusterMI’ version 1.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

clusterMI-package	clusterMI: Cluster Analysis with Missing Values by Multiple Imputation
chooseB	Diagnostic plot for the number of iterations used in the varselbest function
choosem	Graphical investigation for the number of datasets generated by multiple imputation
choosemaxit	Diagnostic plot for the number of iterations used in sequential imputation methods
choosenbclust	Tune the number of clusters according to the partition instability
chooser	Kfold cross-validation for specifying threshold r
clusterMI	Cluster analysis and pooling after multiple imputation
fastnmf	Consensus clustering using non-negative matrix factorization
imputedata	Multiple imputation methods for cluster analysis
overimpute	Overimputation diagnostic plot
prodna	Introduce missing values using a missing completely at random mechanism
varselbest	Variable selection for specifying conditional imputation models
wine	Chemical analysis of wines from three different cultivars