mca: Multiple Correspondence Analysis

In dimensio: Multivariate Data Analysis

Multiple Correspondence Analysis

Description

Computes a multiple correspondence analysis.

Usage

mca(object, ...)

## S4 method for signature 'data.frame'
mca(
  object,
  rank = NULL,
  sup_row = NULL,
  sup_col = NULL,
  sup_quanti = NULL,
  autodetect = FALSE
)

## S4 method for signature 'matrix'
mca(object, rank = NULL, sup_row = NULL, sup_col = NULL)

Arguments

object	A m \times p numeric matrix or a data.frame.
...	Currently not used.
rank	An integer value specifying the maximal number of components to be kept in the results. If NULL (the default), min(m, p) - 1 components will be returned.
sup_row	A vector specifying the indices of the supplementary rows.
sup_col	A vector specifying the indices of the supplementary categorical columns.
sup_quanti	A vector specifying the indices of the supplementary quantitative columns.
autodetect	A logical scalar: should numeric variables be automatically removed (except sup_quanti)?

Value

A MCA object.

Author(s)

N. Frerebeau

References

Lebart, L., Piron, M. and Morineau, A. Statistique exploratoire multidimensionnelle: visualisation et inférence en fouille de données. Paris: Dunod, 2006.

See Also

svd(), cdt()

Other multivariate analysis: ca(), pca(), pcoa(), predict()

dimensio documentation built on April 3, 2025, 10:36 p.m.