{ "_id": "6a3121293efcd9bda435ce67", "Package": "horseshoenlm", "Title": "Nonlinear Regression using Horseshoe Prior", "Version": "0.0.6", "Authors@R": "c(person(\"Arnab Kumar\", \"Maity\", email = \"Arnab.Maity@pfizer.com\", role = c(\"aut\", \"cre\")))", "Description": "Provides the posterior estimates of the regression\ncoefficients when horseshoe prior is specified. The regression\nmodels considered here are logistic model for binary response\nand log normal accelerated failure time model for right\ncensored survival response. The linear model analysis is also\navailable for completeness. All models provide deviance\ninformation criterion and widely applicable information\ncriterion. See Maity et. al. (2019)\n Maity et. al. 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