omcabasic: Ordered multiple correspondence analysis via orthogonal...

View source: R/omcabasic.R

omcabasicR Documentation

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.