ca (version 0.71.1)

ca: Simple correspondence analysis

Description

Computation of simple correspondence analysis.

Usage

ca(obj, ...)
# S3 method for matrix
ca(obj, nd = NA, suprow = NA, supcol = NA, 
   subsetrow = NA, subsetcol = NA, ...)
# S3 method for data.frame
ca(obj, ...)
# S3 method for table
ca(obj, ...)
# S3 method for xtabs
ca(obj, ...)
# S3 method for 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

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

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.

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

# NOT RUN {
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))

 
# }