{
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  "Package": "BinaryEPPM",
  "Type": "Package",
  "Title": "Mean and Scale-Factor Modeling of Under- And Over-Dispersed\nBinary Data",
  "Version": "3.0",
  "Date": "2024-06-03",
  "Authors@R": "c(person(c(\"David\", \"M.\"), \"Smith\", role = c(\"aut\", \"cre\"),\nemail = \"dmccsmith@verizon.net\"),\nperson(c(\"Malcolm\", \"J.\"), \"Faddy\", role = \"aut\"))",
  "Description": "Under- and over-dispersed binary data are modeled using an\nextended Poisson process model (EPPM) appropriate for binary\ndata. A feature of the model is that the under-dispersion\nrelative to the binomial distribution only needs to be greater\nthan zero, but the over-dispersion is restricted compared to\nother distributional models such as the beta and correlated\nbinomials. Because of this, the examples focus on\nunder-dispersed data and how, in combination with the beta or\ncorrelated distributions, flexible models can be fitted to data\ndisplaying both under- and over-dispersion. Using Generalized\nLinear Model (GLM) terminology, the functions utilize linear\npredictors for the probability of success and scale-factor with\nvarious link functions for p, and log link for scale-factor, to\nfit a variety of models relevant to areas such as bioassay.\nDetails of the EPPM are in Faddy and Smith (2012)\n<doi:10.1002/bimj.201100214> and Smith and Faddy (2019)\n<doi:10.18637/jss.v090.i08>.",
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    "User": "root"
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  "Author": "David M. Smith [aut, cre], Malcolm J. Faddy [aut]",
  "Maintainer": "David M. Smith <dmccsmith@verizon.net>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2024-06-05 02:41:28 UTC",
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    "GBprob",
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    "loglog",
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    "Model.GB",
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    "plot.BinaryEPPM",
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    "predict.BinaryEPPM",
    "print.BinaryEPPM",
    "print.summaryBinaryEPPM",
    "residuals.BinaryEPPM",
    "summary.BinaryEPPM",
    "vcov.BinaryEPPM",
    "waldtest.BinaryEPPM"
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      "title": "The data are of the number of male piglets born in litters of varying sizes for the Berkshire breed of pigs.",
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      "title": "Kupper and Haseman example data",
      "object": "KupperHaseman.case",
      "file": "KupperHaseman.case.rda",
      "class": [
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        "Number.Implants"
      ],
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      "table": true,
      "tojson": true
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      "title": "The data are of the number of male piglets born in litters of varying sizes for the Parkes breed of pigs.",
      "object": "Parkes.litters",
      "file": "Parkes.litters.rda",
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      "tojson": true
    },
    {
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      "title": "Dilution series for the presence of rope spores.",
      "object": "ropespores.case",
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        "fdilution",
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        "number.tested"
      ],
      "rows": 10,
      "table": true,
      "tojson": true
    },
    {
      "name": "ropespores.grouped",
      "title": "Dilution series for the presence of rope spores.",
      "object": "ropespores.grouped",
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      "object": "wordcount.case",
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    {
      "page": "BinaryEPPM-package",
      "title": "Mean and Scale-Factor Modeling of Under- And Over-Dispersed Binary Data",
      "topics": [
        "BinaryEPPM-package"
      ]
    },
    {
      "page": "BBprob",
      "title": "Calculation of vector of probabilities for the beta binomial distribution.",
      "topics": [
        "BBprob"
      ]
    },
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      "page": "Berkshires.litters",
      "title": "The data are of the number of male piglets born in litters of varying sizes for the Berkshire breed of pigs.",
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      "page": "BinaryEPPM",
      "title": "Fitting of EPPM models to binary data.",
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    },
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      "title": "Extraction of model coefficients for BinaryEPPM Objects",
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      "title": "Double exponential Link Function",
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      "topics": [
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    },
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      "page": "hatvalues.BinaryEPPM",
      "title": "Extraction of hat matrix values from BinaryEPPM Objects",
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      "title": "Kupper and Haseman example data",
      "topics": [
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      "page": "LL.gradient",
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      "topics": [
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    },
    {
      "page": "LL.Regression.Binary",
      "title": "Function called by optim to calculate the log likelihood from the probabilities and hence perform the fitting of regression models to the binary data.",
      "topics": [
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      "title": "Extract Log-Likelihood",
      "topics": [
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    {
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    },
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      "title": "Function for obtaining output from distributional models.",
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      "topics": [
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      "title": "Negative complementary log-log Link Function",
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    },
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      "page": "Parkes.litters",
      "title": "The data are of the number of male piglets born in litters of varying sizes for the Parkes breed of pigs.",
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      "title": "Diagnostic Plots for BinaryEPPM Objects",
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        "plot.BinaryEPPM"
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      "title": "Power Logit Link Function",
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      "title": "Prediction Method for BinaryEPPM Objects",
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      "title": "Printing of BinaryEPPM Objects",
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      "title": "Summary of BinaryEPPM Objects",
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