omcabasic: Ordered multiple correspondence analysis via orthogonal...

In MCAvariants: Multiple Correspondence Analysis Variants

Ordered multiple correspondence analysis via orthogonal polynomials

Description

This function is used in the main function MCAvariants when the input parameter is catype="omca". It requires that all categorical variables are ordered variables. It performs the hybrid decomposition of the weighted super-indicator matrix and compute polynomial axes, coordinates, weights of rows and columns and total inertia.

Usage

omcabasic(xo,np , nmod , tmod , rows, idr, idc, idcv,vordered)

Arguments

xo	The starting table of variables in reduced code.
np	The column number of the starting table (coincident with the variable number). By default,np=5.
nmod	The number of variable catgories of each variable.
tmod	The total number of variable catgories.
rows	The row number of the starting table (coincident with the individual number).
idr	The row labels of the data table.
idc	The column labels of the data table.
idcv	The labels of the categories of each variable.
vordered	The flag parameter for specifying what variable is ordered. By default, all the five variables are ordered: vordered = c(TRUE,TRUE,TRUE,TRUE,TRUE).

Note

This function belongs to the R object class called mcabasicresults.

Author(s)

Rosaria Lombardo

References

Lombardo R and Meulman JJ (2010) Journal of Classification, 27, 191-210.
Beh EJ Lombardo R (2014) Correspondence Analysis, Theory, Practice and New Strategies. Wiley

MCAvariants documentation built on Aug. 21, 2023, 5:09 p.m.