Cluster Analysis with Missing Values by Multiple Imputation

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Documentation for package ‘clusterMI’ version 1.3

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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