{ "_id": "6a27abb624555f66ed5345be", "Package": "McMiso", "Type": "Package", "Title": "Multicore Multivariable Isotonic Regression", "Version": "0.2.0", "Authors@R": "person(\"Cheung\", \"Ken\", email = \"yc632@cumc.columbia.edu\",\nrole = c(\"aut\", \"cre\"))", "Description": "Provides functions for isotonic regression and\nclassification when there are multiple independent variables.\nThe functions solve the optimization problem using a projective\nBayes approach with recursive sequential update algorithms, and\nare useful for situations with a relatively large number of\ncovariates. Supports binary outcomes via a Beta-Binomial\nconjugate model ('miso', 'PBclassifier') and continuous\noutcomes via a Normal-Inverse-Chi-Squared conjugate model\n('misoN'). Parallel computing wrappers ('mcmiso',\n'mcPBclassifier', 'mcmisoN') are provided that run the down-up\nand up-down algorithms simultaneously and return whichever\nfinishes first. 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