Compute the variance-covariance matrix of parameter estimates of a CUBE model with covariates for all the three parameters.
varcovcubecov(m, ordinal, Y, W, Z, estbet, estgama, estalpha)Number of ordinal categories
Vector of ordinal responses
Matrix of covariates for explaining the uncertainty component
Matrix of covariates for explaining the feeling component
Matrix of covariates for explaining the overdispersion component
Vector of the estimated parameters for the uncertainty component, with length equal to NCOL(Y)+1 to account for an intercept term (first entry)
Vector of the estimated parameters for the feeling component, with length equal to NCOL(W)+1 to account for an intercept term (first entry)
Vector of the estimated parameters for the overdispersion component, with length equal to NCOL(Z)+1 to account for an intercept term (first entry)
The function checks if the variance-covariance matrix is positive-definite: if not, it returns a warning message and produces a matrix with NA entries.
Piccolo, D. (2014), Inferential issues on CUBE models with covariates, Communications in Statistics - Theory and Methods, 44, DOI: 10.1080/03610926.2013.821487