chi2cub: Pearson X^2 statistic

In CUB: A Class of Mixture Models for Ordinal Data

Description

Compute the X^2 statistic of Pearson for CUB models with one or two discrete covariates for the feeling component.

Usage

chi2cub(m,ordinal,W,pai,gama)

Arguments

m	Number of ordinal categories
ordinal	Vector of ordinal responses
W	Matrix of covariates for the feeling component
pai	Uncertainty parameter
gama	Vector of parameters for the feeling component, with length equal to NCOL(W)+1 to account for an intercept term (first entry of gama)

Details

No missing value should be present neither for ordinal nor for covariate matrices: thus, deletion or imputation procedures should be preliminarily run.

Value

A list with the following components:

df	Degrees of freedom
chi2	Value of the Pearson fitting measure
dev	Deviance indicator

References

Tutz, G. (2012). Regression for Categorical Data, Cambridge University Press, Cambridge

Examples

data(univer)
m<-7
pai<-0.3
gama<-c(0.1,0.7)
ordinal<-univer$informat; W<-univer$gender;
pearson<-chi2cub(m,ordinal,W,pai,gama)
degfree<-pearson$df
statvalue<-pearson$chi2
deviance<-pearson$dev

CUB documentation built on March 31, 2020, 5:14 p.m.