{ "_id": "6a10405eacfb0bcc41c9d160", "Package": "mixpoissonreg", "Title": "Mixed Poisson Regression for Overdispersed Count Data", "Version": "1.0.0", "Authors@R": "c(person(given = \"Alexandre B.\",\nfamily = \"Simas\",\nrole = c(\"aut\", \"cre\"),\nemail = \"alexandre.impa@gmail.com\",\ncomment = c(ORCID = \"0000-0003-2562-2829\")),\nperson(given = \"Wagner\",\nfamily = \"Barreto-Souza\",\nrole = \"aut\",\nemail = \"wagnerbs85@gmail.com\",\ncomment = c(ORCID = \"0000-0003-0831-7881\")))", "Maintainer": "Alexandre B. Simas ", "Description": "Fits mixed Poisson regression models (Poisson-Inverse\nGaussian or Negative-Binomial) on data sets with response\nvariables being count data. The models can have varying\nprecision parameter, where a linear regression structure\n(through a link function) is assumed to hold on the precision\nparameter. The Expectation-Maximization algorithm for both\nthese models (Poisson Inverse Gaussian and Negative Binomial)\nis an important contribution of this package. Another important\nfeature of this package is the set of functions to perform\nglobal and local influence analysis. 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