R: Cluster Analysis with Missing Values by Multiple Imputation

# Cluster Analysis with Missing Values by Multiple Imputation

## Documentation for package ‘clusterMI’ version 1.6

- 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