GDAtools (version 1.0)

speMCA: Performs a 'specific' MCA

Description

Performs a 'specific' Multiple Correspondence Analysis, i.e. a variant of MCA that allows to treat undesirable categories as passive categories.

Usage

speMCA(data, excl = NULL, ncp = 5, row.w = rep(1, times = nrow(data)))

Value

• Returns an object of class 'speMCA', i.e. a list including:
• eig
  a list of vectors containing all the eigenvalues, the percentage of variance, the cumulative percentage of variance, the modified rates and the cumulative modified rates
• call
  a list with informations about input data
• ind
  a list of matrices containing the results for the individuals (coordinates, contributions)
• var
  a list of matrices containing all the results for the categories and variables (weights, coordinates, square cosine, categories contributions to axes and cloud, test values (v.test), square correlation ratio (eta2), variable contributions to axes and cloud

Details

Undesirable categories may be of several kinds: infrequent categories (say,

References

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

See Also

getindexcat, plot.speMCA, varsup, contrib, modif.rate, dimdesc.MCA, MCA, csMCA

Examples

## Performs a specific MCA on 'Music' example data set
## ignoring every 'NA' (i.e. 'not available') categories.
data(Music)
getindexcat(Music[,1:5])
mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15))
str(mca)