Main function for CUB models with covariates for both the uncertainty and the feeling components

Share:

Description

Estimate and validate a CUB model for given ordinal responses, with covariates for explaining both the feeling and the uncertainty components by means of logistic transform.

Usage

1
cubpq(m, ordinal, Y, W, maxiter, toler, summary)

Arguments

m

Number of ordinal categories

ordinal

Vector of ordinal responses

Y

Matrix of selected covariates for explaining the uncertainty component

W

Matrix of selected covariates for explaining the feeling component

maxiter

Maximum number of iterations allowed for running the optimization algorithm

toler

Fixed error tolerance for final estimates

summary

Logical: if TRUE, summary results of the fitting procedure are displayed on screen

Value

An object of the class "CUB"

References

Piccolo D. and D'Elia A. (2008), A new approach for modelling consumers' preferences, Food Quality and Preference, 18, 247–259
Iannario M. and Piccolo D. (2010), A new statistical model for the analysis of customer satisfaction, Quality Technology and Quantitative Management, 17(2) 149–168

See Also

varcovcubpq, loglikcubpq, inibestgama, CUB

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.