It provides matrix of probabilities under different parametrizations and for the case of response variables having a different number of categories.
Usage
prob_multi_glob_gen(X, model, be, ind=(1:dim(X)[3]))
Arguments
X
array of all distinct covariate configurations
model
type of logit (g = global, l = local, m = multinomial)
be
initial vector of regression coefficients
ind
vector to link responses to covariates
Value
Pdismatrix of distinct probability vectors
Pmatrix of the probabilities for each covariate configuration
References
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.