{
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  "Package": "gwzinbr",
  "Type": "Package",
  "Title": "Geographically Weighted Zero Inflated Negative Binomial\nRegression",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(\"Jéssica\", \"Vasconcelos\", , \"jehh.vasconcelosabreu@gmail.com\", role=c(\"aut\", \"cre\")),\nperson(\"Juliana\", \"Rosa\", , \"julianamrosa00@gmail.com\", role=\"aut\"),\nperson(\"Alan\", \"da Silva\", , \"alansilva@unb.br\", role=\"aut\"))",
  "Maintainer": "Jéssica Vasconcelos <jehh.vasconcelosabreu@gmail.com>",
  "Description": "Fits a geographically weighted regression model using zero\ninflated probability distributions. Has the zero inflated\nnegative binomial distribution (zinb) as default, but also\naccepts the zero inflated Poisson (zip), negative binomial\n(negbin) and Poisson distributions. Can also fit the global\nversions of each regression model. Da Silva, A. R. & De Sousa,\nM. D. R. (2023). \"Geographically weighted zero-inflated\nnegative binomial regression: A general case for count data\",\nSpatial Statistics <doi:10.1016/j.spasta.2023.100790>.\nBrunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996).\n\"Geographically weighted regression: a method for exploring\nspatial nonstationarity\", Geographical Analysis,\n<doi:10.1111/j.1538-4632.1996.tb00936.x>. Yau, K. K. W., Wang,\nK., & Lee, A. H. (2003). \"Zero-inflated negative binomial mixed\nregression modeling of over-dispersed count data with extra\nzeros\", Biometrical Journal, <doi:10.1002/bimj.200390024>.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
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  "Repository": "https://jessicavasconcelos.r-universe.dev",
  "Date/Publication": "2024-06-02 21:45:55 UTC",
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  "NeedsCompilation": "no",
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    "User": "root"
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  "Author": "Jéssica Vasconcelos [aut, cre],\nJuliana Rosa [aut],\nAlan da Silva [aut]",
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