fast_mca: Multiple Correspondence Analysis
In svs: Tools for Semantic Vector Spaces

fast_mca

R Documentation

Multiple Correspondence Analysis

Description

A fast procedure for computing multiple correspondence analysis.

Usage

fast_mca(dat, nfac = FALSE)

Arguments

`dat`	Input data: has to be a data frame (with any number of columns).
`nfac`	Logical indicating whether the number of factors (i.e. the number of columns in `dat`) is a divisor for the eigenvalues (principal inertias) and the coordinates.

Value

A list with components:

`val`	The eigenvalues or principal inertias, indicating how much each latent axis explains.
`pos`	The coordinates of all levels.

References

Greenacre, M. (2017) Correspondence analysis in practice, Third edition. Boca Raton: Chapman and Hall/CRC.

Examples

SndT_Fra <- read.table(system.file("extdata", "SndT_Fra.txt", package = "svs"),
   header = TRUE, sep = "\t", quote = "\"", encoding = "UTF-8",
   stringsAsFactors = FALSE)
mca_SndT_Fra <- fast_mca(SndT_Fra)
mca_SndT_Fra

svs documentation built on June 24, 2024, 5:07 p.m.