varcovcubecov function

Variance-covariance matrix of a CUBE model with covariates

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)

Arguments

• m: Number of ordinal categories
• ordinal: Vector of ordinal responses
• Y: Matrix of covariates for explaining the uncertainty component
• W: Matrix of covariates for explaining the feeling component
• Z: Matrix of covariates for explaining the overdispersion component
• estbet: Vector of the estimated parameters for the uncertainty component, with length equal to NCOL(Y)+1 to account for an intercept term (first entry)
• estgama: Vector of the estimated parameters for the feeling component, with length equal to NCOL(W)+1 to account for an intercept term (first entry)
• estalpha: Vector of the estimated parameters for the overdispersion component, with length equal to NCOL(Z)+1 to account for an intercept term (first entry)

Details

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.

References

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