ca: Simple correspondence analysis

In ca: Simple, Multiple and Joint 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))

 

ca documentation built on May 2, 2019, 6:12 p.m.