R: Simple correspondence analysis

ca {ca} | R Documentation

## 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.

### See Also

`svd`, `plot.ca`, `plot3d.ca`, `summary.ca`, `print.ca`

### 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))

[Package ca version 0.70 Index]