cubecov | R Documentation |
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)
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 |
An object of the class "CUBE"
Piccolo, D. (2014). Inferential issues on CUBE models with covariates, Communications in Statistics - Theory and Methods, 44, DOI: 10.1080/03610926.2013.821487
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