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hmmm: Hierarchical Multinomial Marginal Models
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.
Getting started
Browse package contents
Package details |
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| Author | Colombi Roberto and Sabrina Giordano and Manuela Cazzaro, with contributions from Joseph Lang |
| Maintainer | Colombi Roberto <colombi@unibg.it> |
| License | GPL (>= 2) |
| Version | 1.0-4 |
| URL | https://www.r-project.org |
| Package repository | View on CRAN |
| Installation |
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