effecube

Vector of initial estimates for the feeling and the overdispersion parameters

paravec

Matrix binding together a column vector of length $m$ containing the posterior
probabilities that each observed category has been generated by the first component distribution 
of the mixture, and the column vector of the absolute frequencies of the observations

dati


Define the opposite of the scalar function that is maximized when running the E-M 
algorithm for CUBE models without covariates.


internal

Estimate and test models for ordinal data concerning the family of
CUB models and their extensions (where CUB stands for Combination of a
discrete Uniform and a shifted Binomial distributions).

effecube: Auxiliary function for the log-likelihood estimation of CUBE models without covariates

Description

Usage

Arguments

Details

References