{ "_id": "6a1edab1b401979e7340f647", "Package": "flexCountReg", "Type": "Package", "Title": "Estimation of a Variety of Count Regression Models", "Version": "0.1.1", "Authors@R": "c(person(\"Jonathan\", \"Wood\", role = c(\"aut\", \"cre\"),\nemail = \"jwood2@iastate.edu\",\ncomment = c(ORCID = \"0000-0003-0131-6384\")),\nperson(\"Guillermo\", \"Basulto-Elias\", role = c(\"aut\"),\nemail = \"basulto@iastate.edu\",\ncomment = c(ORCID = \"0000-0002-5205-2190\")))", "Maintainer": "Jonathan Wood ", "Description": "An implementation of multiple regression models for count\ndata. These include various forms of the negative binomial\n(NB-1, NB-2, NB-P, generalized negative binomial, etc.),\nPoisson-Lognormal, other compound Poisson distributions, the\nGeneralized Waring model, etc. Information on the different\nforms of the negative binomial are described by Greene (2008)\n. For treatises on count\nmodels, see Cameron and Trivedi (2013)\n and Hilbe (2012)\n. For the implementation of\nunder-reporting in count models, see Wood et al. (2016)\n. For prediction methods in\nrandom parameter models, see Wood and Gayah (2025)\n. For estimating random\nparameters using maximum simulated likelihood, see Greene and\nHill (2010) ; Gourieroux and\nMonfort (1996) ; or Hensher et\nal. 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