Package: hmmm
Version: 1.0-1
Date: 2013-02-14
Title: hierarchical multinomial marginal models
Authors@R: c(person(given = "Roberto", family = "Colombi", role =
c("aut", "cre"), email = "colombi@unibg.it"), person(given =
"Sabrina", family = "Giordano", role = "aut", email =
"sabrina.giordano@unical.it"), person(given = "Manuela", family
= "Cazzaro", role = "aut", email =
"manuela.cazzaro@unimib.it"), person(given = "Joseph B.",
family = "Lang", role = "ctb"))
Maintainer: Colombi Roberto <colombi@unibg.it>
Description: Functions for specifying and fitting marginal models for
contingency tables proposed by Bergsma and Rudas (2002) here
called hierarchical multinomial marginal models (hmmm) and
their extensions presented by Bartolucci et al.  (2007);
multinomial Poisson homogeneous (mph) models and homogeneous
linear predictor (hlp) models for contingency tables proposed
by Lang (2004) and (2005); hidden Markov models where the
distribution of the observed variables is described by a
marginal model.  Inequality constraints on the parameters are
allowed and can be tested.
Depends: quadprog, MASS
License: GPL (>= 2)
Packaged: 2013-02-15 15:01:48 UTC; Sabrina
Author: Roberto Colombi [aut, cre], Sabrina Giordano [aut], Manuela
Cazzaro [aut], Joseph B. Lang [ctb]
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-02-15 17:02:42

Author: Colombi Roberto and Sabrina Giordano and Manuela Cazzaro, with  contributions from Joseph Lang
Description: Functions for specifying and fitting marginal models for contingency tables proposed
by Bergsma and Rudas (2002) here called hierarchical multinomial marginal models (hmmm) and their extensions presented by Bartolucci et al.
(2007); multinomial Poisson homogeneous (mph) models and homogeneous linear predictor (hlp) models for contingency
tables proposed by Lang (2004) and (2005); hidden Markov models where the distribution of the observed variables
Inequality constraints on the parameters are allowed and can be tested.

Author: Colombi Roberto and Sabrina Giordano and Manuela Cazzaro, with contributions from Joseph Lang