mca

0th

Percentile

Multiple Correspondence Analysis

Computes a multiple correspondence analysis of a set of factors.

Keywords
multivariate, category
Usage
mca(df, nf = 2, abbrev = FALSE)
Arguments
df
A data frame containing only factors
nf
The number of dimensions for the MCA. Rarely 3 might be useful.
abbrev
Should the vertex names be abbreviated? By default these are of the form factor.level but if abbrev = TRUE they are just level which will suffice if the factors have distinct levels.
Value

  • An object of class "mca", with components
  • rsThe coordinates of the rows, in nf dimensions.
  • csThe coordinates of the column vertices, one for each level of each factor.
  • fsWeights for each row, used to interpolate additional factors in predict.mca.
  • pThe number of factors
  • dThe singular values for the nf dimensions.
  • callThe matched call.

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

predict.mca, plot.mca, corresp

Aliases
  • mca
  • print.mca
Examples
farms.mca <- mca(farms, abbrev=TRUE)
farms.mca
plot(farms.mca)
Documentation reproduced from package MASS, version 7.3-19, License: GPL-2 | GPL-3

Community examples

Looks like there are no examples yet.