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  "Title": "Empirical Bayesian Tobit Matrix Estimation",
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  "Date": "2024-05-03",
  "Authors@R": "c(\nperson(\"Alton\", \"Barbehenn\", , \"altonbarbehenn@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0009-0000-3364-7204\")),\nperson(\"Sihai Dave\", \"Zhao\", , \"sdzhao@illinois.edu\", role = \"aut\")\n)",
  "Description": "Estimation tools for multidimensional Gaussian means using\nempirical Bayesian g-modeling. Methods are able to handle fully\nobserved data as well as left-, right-, and interval-censored\nobservations (Tobit likelihood); descriptions of these methods\ncan be found in Barbehenn and Zhao (2023)\n<doi:10.48550/arXiv.2306.07239>. Additional, lower-level\nfunctionality based on Kiefer and Wolfowitz (1956)\n<doi:10.1214/aoms/1177728066> and Jiang and Zhang (2009)\n<doi:10.1214/08-AOS638> is provided that can be used to\naccelerate many empirical Bayes and nonparametric maximum\nlikelihood problems.",
  "License": "GPL-3",
  "URL": "https://github.com/barbehenna/ebTobit",
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  "Author": "Alton Barbehenn [aut, cre]\n(<https://orcid.org/0009-0000-3364-7204>), Sihai Dave Zhao\n[aut]",
  "Maintainer": "Alton Barbehenn <altonbarbehenn@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2024-05-04 02:33:10 UTC",
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    "tobit_sd",
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      "page": "BileAcid",
      "title": "Bile Acid Data",
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      "title": "Convex Optimization of the Kiefer-Wolfowitz NPMLE",
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    },
    {
      "page": "ConvexPrimal",
      "title": "Convex Optimization of the Kiefer-Wolfowitz NPMLE",
      "topics": [
        "ConvexPrimal"
      ]
    },
    {
      "page": "ebTobit",
      "title": "Empirical Bayes Matrix Estimation under a Tobit Likelihood",
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        "ebTobit"
      ]
    },
    {
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      "title": "Nonparametric Maximum Likelihood via Expectation Maximization",
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