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ca

Simple correspondence analysis

Description

Computation of simple correspondence analysis.

Usage

ca(obj, ...)

## S3 method for class 'matrix'
ca(obj, nd = NA, suprow = NA, supcol = NA, 
   subsetrow = NA, subsetcol = NA, ...)

## S3 method for class 'data.frame'
ca(obj, ...)

## S3 method for class 'table'
ca(obj, ...)

## S3 method for class 'xtabs'
ca(obj, ...)

## S3 method for class 'formula'
ca(formula, data, ...)

Arguments

`obj,formula`	The function is generic, accepting various forms of the principal argument for specifying a two-way frequency table. Currently accepted forms are matrices, data frames (coerced to frequency tables), objects of class `"xtabs"` or `"table"` and one-sided formulae of the form `~ F1 + F2`, where `F1` and `F2` are factors.
`nd`	Number of dimensions to be included in the output; if NA the maximum possible dimensions are included.
`suprow`	Indices of supplementary rows.
`supcol`	Indices of supplementary columns.
`subsetrow`	Row indices of subset.
`subsetcol`	Column indices of subset.
`data`	A data frame against which to preferentially resolve variables in the `formula`
`...`	Other arguments passed to the `ca.matrix` method

Details

The function ca computes a simple correspondence analysis based on the singular value decomposition.
The options suprow and supcol allow supplementary (passive) rows and columns to be specified. Using the options subsetrow and/or subsetcol result in a subset CA being performed.

Value

`sv`	Singular values
`nd`	Dimenson of the solution
`rownames`	Row names
`rowmass`	Row masses
`rowdist`	Row chi-square distances to centroid
`rowinertia`	Row inertias
`rowcoord`	Row standard coordinates
`rowsup`	Indices of row supplementary points
`colnames`	Column names
`colmass`	Column masses
`coldist`	Column chi-square distances to centroid
`colinertia`	Column inertias
`colcoord`	Column standard coordinates
`colsup`	Indices of column supplementary points
`N`	The frequency table

References

Nenadic, O. and Greenacre, M. (2007). Correspondence analysis in R, with two- and three-dimensional graphics: The ca package. Journal of Statistical Software, 20 (3), http://www.jstatsoft.org/v20/i03/

Greenacre, M. (2007). Correspondence Analysis in Practice. Second Edition. London: Chapman & Hall / CRC. Blasius, J. and Greenacre, M. J. (1994), Computation of correspondence analysis, in Correspondence Analysis in the Social Sciences, pp. 53-75, London: Academic Press.

Greenacre, M.J. and Pardo, R. (2006), Subset correspondence analysis: visualizing relationships among a selected set of response categories from a questionnaire survey. Sociological Methods and Research, 35, pp. 193-218.

Examples

data("author")
ca(author)
plot(ca(author))

# table method
haireye <- margin.table(HairEyeColor, 1:2)
haireye.ca <- ca(haireye)
haireye.ca
plot(haireye.ca)
# some plot options
plot(haireye.ca, lines=TRUE)
plot(haireye.ca, arrows=c(TRUE, FALSE))

ca

Simple, Multiple and Joint Correspondence Analysis

v0.71.1

GPL

Authors

Michael Greenacre [aut], Oleg Nenadic [aut, cre], Michael Friendly [ctb]

Initial release

2018-10-10

ca