Hierarchical Multinomial Marginal Models
akaike criterium
anova for the class hmmmfit
design matrix for a hmm model
vector of frequencies from a data frame
Function to compute the generalized marginal interactions associated t...
summary for hmmm.chibar
package hmmm
chi-bar statistic test for hmm models
fit a hmm model
define a hmm model
hmm model with covariates effect on parameters
Function to compute a vector of joint probabilities from a vector of g...
define a log-linear model
lists of marginal sets
fit mph models under inequality constraints
print for hmmm.chibar
print for the class hmmmfit
recursive marginal interactions
summary for the class hmmmfit
summary and print for the class hmmmmod
summary and print for the class mphfit
Functions for specifying and fitting marginal models for contingency tables proposed by Bergsma and Rudas (2002) <doi:10.1214/aos/1015362188> here called hierarchical multinomial marginal models (hmmm) and their extensions presented by Bartolucci, Colombi and Forcina (2007) <https://www.jstor.org/stable/24307737>; multinomial Poisson homogeneous (mph) models and homogeneous linear predictor (hlp) models for contingency tables proposed by Lang (2004) <doi:10.1214/aos/1079120140> and Lang (2005) <doi:10.1198/016214504000001042>. Inequality constraints on the parameters are allowed and can be tested.