cube000: Main function for CUBE models without covariates

In CUB: A Class of Mixture Models for Ordinal Data

Description

Estimate and validate a CUBE model without covariates.

Usage

cube000(m, ordinal, starting, maxiter, toler, expinform)

Arguments

m	Number of ordinal categories
ordinal	Vector of ordinal responses
starting	Vector of initial estimates to start the optimization algorithm, whose length equals the number of parameters of the model
maxiter	Maximum number of iterations allowed for running the optimization algorithm
toler	Fixed error tolerance for final estimates
expinform	Logical: if TRUE, the function returns the expected variance-covariance matrix

Value

An object of the class "CUBE"

References

Iannario, M. (2014). Modelling Uncertainty and Overdispersion in Ordinal Data, Communications in Statistics - Theory and Methods, 43, 771–786
Iannario, M. (2015). Detecting latent components in ordinal data with overdispersion by means of a mixture distribution, Quality & Quantity, 49, 977–987

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