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  "Title": "Regularized Parametric Modal Regression: Lasso, Elastic Net and\nRidge",
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  "Authors@R": "c(\nperson(\"Christian E.\", \"Galarza\", email = \"chedgala@espol.edu.ec\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-4818-6006\",\naffiliation = \"Escuela Superior Politécnica del Litoral, Guayaquil, Ecuador\")),\nperson(\"Víctor H.\", \"Lachos\", email = \"hlachos@uconn.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-7239-2459\",\naffiliation = \"University of Connecticut, Storrs, CT, USA\")),\nperson(\"Dashun\", \"Liu\", email = \"dashun.liu@uconn.edu\", role = \"aut\",\ncomment = c(affiliation = \"University of Connecticut, Storrs, CT, USA\")))",
  "Description": "Variable selection and estimation for parametric modal\nregression with continuous positive responses (Gamma, Weibull\nand Lognormal families) under Lasso, elastic-net, ridge and\nadaptive-Lasso penalties. The conditional mode is linked to a\nlinear predictor through a logarithmic link using the mode\nreparameterization of Galarza and Lachos (2026)\n<doi:10.48550/arXiv.2603.07099>. The penalized log-likelihood\nis maximized with a proximal Newton algorithm (iteratively\nreweighted penalized least squares): at each iteration the\nmodal log-likelihood is replaced by a local quadratic surrogate\nin the linear predictor, which yields a pseudo-response and a\nworking weight in closed form, and the resulting weighted\npenalized least-squares subproblem is solved by the\ncoordinate-descent solver of 'glmnet' (Friedman, Hastie and\nTibshirani, 2010, <doi:10.18637/jss.v033.i01>). The\nregularization parameter is chosen along a warm-started path by\nthe extended Bayesian information criterion of Chen and Chen\n(2008) <doi:10.1093/biomet/asn034>.",
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  "URL": "https://github.com/chedgala/ModalNet",
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  "Date/Publication": "2026-10-22 04:44:34 UTC",
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  "Author": "Christian E. Galarza [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-4818-6006>, affiliation: Escuela\nSuperior Politécnica del Litoral, Guayaquil, Ecuador),\nVíctor H. Lachos [aut] (ORCID: <https://orcid.org/0000-0002-7239-2459>,\naffiliation: University of Connecticut, Storrs, CT, USA),\nDashun Liu [aut] (affiliation: University of Connecticut, Storrs, CT,\nUSA)",
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  "_created": "2026-11-05T01:22:47.000Z",
  "_published": "2026-11-05T01:25:24.643Z",
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      "title": "Riboflavin production in Bacillus subtilis (100 most variable genes)",
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      "title": "Penalized parametric modal regression for positive responses",
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        "modal_net"
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      "title": "Methods for ModalNet fits",
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        "fitted.ModalNet",
        "logLik.ModalNet",
        "ModalNet-methods",
        "print.ModalNet",
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