Sequential Mosaics and Strucplots for an N-way Table

This function takes an n-way contingency table and plots mosaics for series of sequential models to the 1-, 2-, ... n-way marginal tables, corresponding to a variety of types of loglinear models.

Usage

seq_mosaic(x, panel = mosaic, 
   type = c("joint", "conditional", "mutual", "markov", "saturated"), 
   plots = 1:nf, vorder = 1:nf, 
   k = NULL, ...)

Arguments

x: a contingency table in array form, with optional category labels specified in the dimnames(x) attribute, or else a data.frame in frequency form, with the frequency variable named "Freq".
panel: a strucplot panel function, typically mosaic or sieve. NOT yet implemented.
type: type of sequential model to fit, a character string. One of "joint", "conditional", "mutual", "markov", or "saturated".
plots: which marginal sub-tables to plot? A vector of a (sub)set of the integers, 1:nf where nf is the number of factors in the full n-way table.
vorder: order of variables, a permutation of the integers 1:nf, used to reorder the variables in the original table for the purpose of fitting sequential marginal models.
k: conditioning variable(s) for type = "joint", "conditional" or Markov chain order for type = "markov"
...: other arguments passed to mosaic.

Details

This function produces similar plots to the use of mosaic.loglmlist, called with the result of seq_loglm.

Value

None. Used for its side-effect of producing plots

References

These functions were inspired by the original SAS implementation of mosaic displays, described in the User's Guide for Mosaics, http://www.datavis.ca/mosaics/mosaics.pdf

Author

Michael Friendly

Examples


data(Titanic, package="datasets")

seq_mosaic(Titanic)  # models of joint independence, Survived last




seq_mosaic(Titanic, type="condit")




seq_mosaic(Titanic, type="mutual")





# other panel functions and options: presently BUGGED
if (FALSE) { # \dontrun{
seq_mosaic(Titanic, type="mutual", panel=sieve, 
   gp=shading_Friendly, labeling=labeling_values)
} # }