cubecov function

Main function for CUBE models with covariates

Function to estimate and validate a CUBE model with explicative covariates for all the three parameters.

cubecov(m, ordinal, Y, W, Z, starting, maxiter, toler)

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
• Z: Matrix of selected covariates for explaining the overdispersion component
• starting: Vector of initial parameters estimates to start the optimization algorithm (it has length NCOL(Y) + NCOL(W) + NCOL(Z) + 3 to account for intercept terms for all the three components
• maxiter: Maximum number of iterations allowed for running the optimization algorithm
• toler: Fixed error tolerance for final estimates

Returns

An object of the class "CUBE"

References

Piccolo, D. (2014). Inferential issues on CUBE models with covariates, Communications in Statistics - Theory and Methods, 44 , DOI: 10.1080/03610926.2013.821487