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  "Title": "Elicitation of Independent Conditional Means Priors for\nGeneralised Linear Models",
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  "Date": "2022-02-09",
  "Author": "Geoffrey R. Hosack",
  "Maintainer": "Geoff Hosack <geoff.hosack@csiro.au>",
  "Description": "Functions are provided to facilitate prior elicitation for\nBayesian generalised linear models using independent\nconditional means priors. The package supports the elicitation\nof multivariate normal priors for generalised linear models.\nThe approach can be applied to indirect elicitation for a\ngeneralised linear model that is linear in the parameters. The\npackage is designed such that the facilitator executes\nfunctions within the R console during the elicitation session\nto provide graphical and numerical feedback at each design\npoint. Various methodologies for eliciting fractiles\n(equivalently, percentiles or quantiles) are supported,\nincluding versions of the approach of Hosack et al. (2017)\n<doi:10.1016/j.ress.2017.06.011>. For example, experts may be\nasked to provide central credible intervals that correspond to\na certain probability. Or experts may be allowed to vary the\nprobability allocated to the central credible interval for each\ndesign point. Additionally, a median may or may not be\nelicited.",
  "License": "GPL-3",
  "RoxygenNote": "7.1.2",
  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
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  "Date/Publication": "2022-02-09 04:30:02 UTC",
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    "dGompertzNorm",
    "dLogitNorm",
    "elicitPt",
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    "muSigma",
    "mV",
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      "title": "Function to check condition number diagnostic.",
      "topics": [
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    },
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      "title": "Create list with information for the elicitation session",
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      "title": "density for Gompertz transformed univariate Gaussian",
      "topics": [
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    {
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      "title": "density for logit transformed univariate Gaussian",
      "topics": [
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      "title": "Function to create or update elicitation at a given design point.",
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    },
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      "page": "indirect",
      "title": "indirect: A package for assisting indirect elicitation of priors for generalised linear models.",
      "topics": [
        "indirect"
      ]
    },
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      "title": "Function to create summary document from a saved elicitation record.",
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    },
    {
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      "title": "Function to estimate mean and covariance for unknown parameters beta.",
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    {
      "page": "mV",
      "title": "Helper function that translates elicited quantiles of target into independent conditional means normal prior for a defined inverse link function.",
      "topics": [
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      ]
    },
    {
      "page": "pdist",
      "title": "Helper function that gives the probability distribution function for design point.",
      "topics": [
        "pdist"
      ]
    },
    {
      "page": "plotDesignPoint",
      "title": "Plot elicited data, fitted marginals or model output",
      "topics": [
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      ]
    },
    {
      "page": "saveRecord",
      "title": "Function to save elicitation record.",
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      ]
    }
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    "caTools",
    "gplots",
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      "title": "Indirect prior elicitation for Bayesian generalised linear models",
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      "created": "2018-04-06 11:42:33",
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