CA: Correspondence Analysis (CA)

In fdm2id: Data Mining and R Programming for Beginners

Correspondence Analysis (CA)

Description

Performs Correspondence Analysis (CA) including supplementary row and/or column points.

Usage

CA(
  d,
  ncp = ca.ncp(d, row.sup, col.sup, quanti.sup, quali.sup),
  row.sup = NULL,
  col.sup = NULL,
  quanti.sup = NULL,
  quali.sup = NULL,
  row.w = NULL
)

Arguments

d	A data frame or a table with n rows and p columns, i.e. a contingency table.
ncp	The number of dimensions kept in the results. All of them, by default: a table of I active rows by J active columns carries min (I, J) - 1 of them, the first dimension of a contingency table being its margins, which hold no association.
row.sup	A vector indicating the indexes of the supplementary rows.
col.sup	A vector indicating the indexes of the supplementary columns.
quanti.sup	A vector indicating the indexes of the supplementary continuous variables.
quali.sup	A vector indicating the indexes of the categorical supplementary variables.
row.w	An optional row weights (by default, a vector of 1 for uniform row weights); the weights are given only for the active individuals.

Value

The CA on the dataset.

See Also

CA, MCA, PCA, plot.factorial, factorial-class

Examples

data (children, package = "FactoMineR")
CA (children, row.sup = 15:18, col.sup = 6:8)

fdm2id documentation built on Aug. 28, 2026, 9:07 a.m.