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  "Title": "Helper Functions for Bayesian Kernel Machine Regression",
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  "Authors@R": "c(\nperson(\"Kazi Tanvir\", \"Hasan\", , \"khasa006@fiu.edu\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-7723-4177\")),\nperson(\"Ibrahimou\", \"Boubakari\", , \"bibrahim@fiu.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-3173-4317\")),\nperson(\"Guerini\", \"Cristian\", , \"cristian.guerini@unibs.it\", role = \"aut\",\ncomment = c(ORCID = \"0009-0004-4480-5182\")),\nperson(\"Bursac\", \"Zoran\", , \"zbursac@fiu.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-9306-0907\")),\nperson(\"Roberto\", \"Lucchini\", , \"rlucchin@fiu.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-9723-0237\")),\nperson(\"Gabriel\", \"Odom\", , \"gabriel.j.odom@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-1341-4555\"))\n)",
  "Description": "Provides a suite of helper functions to support Bayesian\nKernel Machine Regression (BKMR) analyses in environmental\nhealth research. It enables the simulation of realistic\nmultivariate exposure data using Multivariate Skewed Gamma\ndistributions, estimation of distributional parameters by\nsubgroup, and application of adaptive, data-driven thresholds\nfor feature selection via Posterior Inclusion Probabilities\n(PIPs). It is especially suited for handling skewed exposure\ndata and enhancing the interpretability of BKMR results through\nprincipled variable selection. The methodology is shown in\nHasan et. al. (2025) <doi:10.1101/2025.04.14.25325822>.",
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  "Date/Publication": "2025-05-18 04:29:24 UTC",
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  "Author": "Kazi Tanvir Hasan [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-7723-4177>),\nIbrahimou Boubakari [aut] (ORCID:\n<https://orcid.org/0000-0003-3173-4317>),\nGuerini Cristian [aut] (ORCID: <https://orcid.org/0009-0004-4480-5182>),\nBursac Zoran [aut] (ORCID: <https://orcid.org/0000-0001-9306-0907>),\nRoberto Lucchini [aut] (ORCID: <https://orcid.org/0000-0002-9723-0237>),\nGabriel Odom [aut] (ORCID: <https://orcid.org/0000-0003-1341-4555>)",
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        "age",
        "QI",
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        "Mercury",
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