mjca: Multiple and joint correspondence analysis

Description

Computation of multiple and joint correspondence analysis.

Usage

mjca(obj, nd = 2, lambda = "adjusted", supcol = NA, maxit = 50, epsilon = 0.0001)

Arguments

obj

A response pattern matrix containing factors.

Number of dimensions to be included in the output; if NA the maximum possible dimensions are included.

lambda

Gives the scaling method. Possible values include "indicator", "Burt", "adjusted" and "JCA". Using lambda = "JCA" results in a joint correspondence analysis using iterative adjusment of the Burt matrix in the solution space.

supcol

Indices of supplementary columns.

maxit

The maximum number of iterations (Joint Correspondence Analysis).

epsilon

A convergence criterion (Joint Correspondence Analysis).

Value

svEigenvalues (lambda = "indicator") or singular values (lambda = "Burt", "adjusted" or "JCA")
lambdaScaling method
inertia.ePercentages of explained inertia
inertia.tTotal inertia
inertia.etTotal percentage of explained inertia with the nd-dimensional solution
levelnamesNames of the factor/level combinations
levels.nNumber of levels in each factor
ndUser-specified dimensionality of the solution
nd.maxMaximum possible dimensionality of the solution
rownamesRow names
rowmassRow masses
rowdistRow chi-square distances to centroid
rowinertiaRow inertias
rowcoordRow standard coordinates
colnamesColumn names
colmassColumn masses
coldistColumn chi-square distances to centroid
colinertiaColumn inertias
colcoordColumn standard coordinates
colsupIndices of column supplementary points (of the Burt and Indicator matrix)
BurtBurt matrix
Burt.updThe updated Burt matrix (JCA only)
subinertiaInertias of sub-matrices
JCA.iterVector of length two containing the number of iterations and the epsilon (JCA only)
callReturn of match.call

Details

The function mjca computes a multiple or joint correspondence analysis based on the eigenvalue decomposition of the Burt matrix.

Examples

Run this code

library(MASS)
data(farms)
mjca(farms)

# Joint correspondence analysis:
mjca(farms, lambda = "JCA")

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