doclusterkmeansnone

<p>internally provided by <code>doclusterkmeans</code> function.</p>

data

metriccent

inertiapower

centpos

initcl

<p><code>doclusterkmeansnone</code> performs K-means clustering without variable
  selection.</p>

internal

Implementation of a framework for cluster analysis with selection of the
final number of clusters and an optional variable selection procedure. The package
is designed to integrate the results of multiple imputed datasets while accounting
for the uncertainty that the imputations introduce in the final results. In addition,
the package can also be used for a cluster analysis of the complete cases of a single
dataset. The package also includes specific methods to summarize and plot the results.
The methods are described in Basagana et al. (2013) <doi:10.1093/aje/kws289>.

Jose Barrera-Gomez

miclust

Multiple Imputation in Cluster Analysis

Xavier Basagana

doclusterkmeansnone function

Performs K-means without variable selection. — doclusterkmeansnone

Performs K-means without variable selection.

doclusterkmeansnone: Performs K-means without variable selection.

Description

Usage

Arguments

Value