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 |
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 |
... |
Other arguments passed to the |
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))