It provides matrix of probabilities under different parametrizations.
prob_multi_glob(X, model, be, ind=(1:dim(X)[3]))
array of all distinct covariate configurations
type of logit (g = global, l = local, m = multinomial)
initial vector of regression coefficients
vector to link responses to covariates
matrix of distinct probability vectors
matrix of the probabilities for each covariate configuration
Colombi, R. and Forcina, A. (2001), Marginal regression models for the analysis of positive association of ordinal response variables, Biometrika, 88, 1007-1019.
Glonek, G. F. V. and McCullagh, P. (1995), Multivariate logistic models, Journal of the Royal Statistical Society, Series B, 57, 533-546.