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  "Package": "FlexReg",
  "Title": "Regression Models for Bounded Continuous and Discrete Responses",
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  "Authors@R": "c(person(given = \"Roberto\",\nfamily = \"Ascari\",\nrole = c(\"aut\", \"cre\"),\nemail = \"roberto.ascari@unimib.it\"),\nperson(given = c(\"Agnese\", \"M.\"),\nfamily = \"Di Brisco\",\nrole = \"aut\"),\nperson(given = \"Sonia\",\nfamily = \"Migliorati\",\nrole = \"aut\"),\nperson(given = \"Andrea\",\nfamily = \"Ongaro\",\nrole = \"aut\"))",
  "Description": "Functions to fit regression models for bounded continuous\nand discrete responses. In case of bounded continuous responses\n(e.g., proportions and rates), available models are the\nflexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A.\n(2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di\nBrisco, A. M., Migliorati, S., Ongaro, A. (2020)\n<doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P.,\nCribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), and\ntheir augmented versions to handle the presence of zero/one\nvalues (Di Brisco, A. M., Migliorati, S. (2020)\n<doi:10.1002/sim.8406>) are implemented. In case of bounded\ndiscrete responses (e.g., bounded counts, such as the number of\nsuccesses in n trials), available models are the flexible\nbeta-binomial (Ascari, R., Migliorati, S. (2021)\n<doi:10.1002/sim.9005>), the beta-binomial, and the binomial\nare implemented. Inference is dealt with a Bayesian approach\nbased on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman,\nA., Carlin, J. B., Stern, H. S., Rubin, D. B. (2014)\n<doi:10.1201/b16018>). Besides, functions to compute residuals,\nposterior predictives, goodness of fit measures, convergence\ndiagnostics, and graphical representations are provided.",
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