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  "Title": "Efficient Sampling on the Simplex",
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  "Date": "2017-08-09",
  "Author": "Hannah Director, Scott Vander Wiel, James Gattiker",
  "Maintainer": "Scott Vander Wiel <scottv@lanl.gov>",
  "Description": "The SALTSampler package facilitates Monte Carlo Markov\nChain (MCMC) sampling of random variables on a simplex. A\nSelf-Adjusting Logit Transform (SALT) proposal is used so that\nsampling is still efficient even in difficult cases, such as\nthose in high dimensions or with parameters that differ by\norders of magnitude. Special care is also taken to maintain\naccuracy even when some coordinates approach 0 or 1\nnumerically. Diagnostic and graphic functions are included in\nthe package, enabling easy assessment of the convergence and\nmixing of the chain within the constrained space.",
  "License": "BSD_3_clause + file LICENSE",
  "RoxygenNote": "6.0.1",
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  "Date/Publication": "2017-08-10 18:35:03 UTC",
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      "title": "Efficient Sampling on the Simplex",
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        "SALTSampler-package",
        "SALTSampler"
      ]
    },
    {
      "page": "Diagnostics",
      "title": "Plots and Summaries of RunMh Output",
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    },
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      "title": "Synthetic Data From a Multinomial Distribution",
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      "topics": [
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      ]
    },
    {
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      "title": "Finds logit(sp)",
      "topics": [
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    },
    {
      "page": "LogitSum",
      "title": "Log of the Sum of Probabilities",
      "topics": [
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      "title": "Computes log(p) and log(1-p)",
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    },
    {
      "page": "PropStep",
      "title": "Draw a Proposal on a Simplex",
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      "title": "Metropolis Hasting Algorithm Constrained on a Simplex",
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