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  "Title": "Tilted Bootstrap",
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  "Authors@R": "c(\nperson(\nfamily = \"Morris\",\ngiven = \"Nathan\",\nemail = \"morris_nathan@lilly.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\nfamily = \"Landau\",\ngiven = c(\"William\", \"Michael\"),\nemail = \"will.landau@lilly.com\",\nrole = c(\"aut\")),\nperson(\nfamily = \"Eli Lilly and Company\",\nrole = \"cph\"))",
  "Description": "The tilted bootstrap as implemented in the 'tboot' package\nis an approach to resampling where samples are drawn from the\nobserved data with some samples appearing more frequently than\nothers. Tilted bootstraping may be used to create simulated\nclinical trail data with realistic correlation structures and\nassumed efficacy levels. The 'tboot' package may also be used\nfor simulating a joint Bayesian distribution along along with\nclinical trials based on the Bayesian distribution.",
  "License": "GPL-3",
  "VignetteBuilder": "knitr",
  "URL": "https://github.com/nmorris-lilly/tboot",
  "BugReports": "https://github.com/nmorris-lilly/tboot/issues",
  "RoxygenNote": "7.0.2",
  "Repository": "https://njm18.r-universe.dev",
  "Date/Publication": "2020-07-16 01:04:14 UTC",
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      "title": "tboot: tilted bootstrapping and Bayesian marginal reconstruction.",
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      "topics": [
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      "title": "Bayesian Marginal Reconstruction Simulations",
      "author": "Nathan Morris",
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      "headings": [
        "Introduction",
        "The Example Scenario and Simulated Datasets",
        "The Posterior from BMR and Full Bayesian Analysis are Similar",
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        "Simulation 1: exponential family density",
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      "title": "Getting Started with the Tilted Bootstrap",
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        "Example 1: Constraining the mean for all variables in the data",
        "Example 2: Constraining the mean for a subset of the variables",
        "Example 3: Constraining the mean and variance for a variable",
        "Methodology",
        "Stating the optimization problem",
        "Solving the optimization problem",
        "Problems encountered for some data",
        "Not full rank",
        "Constraint not achievable",
        "Unable to find an optimum",
        "Some samples have a very high weight",
        "Augmented Sampling to Improved Stability",
        "Bibliography"
      ],
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