{
  "_id": "6ab26caf3d719c1f8408d69c",
  "Package": "fitPS",
  "Type": "Package",
  "Title": "Fit Probability Models to Forensic Survey Data",
  "Version": "1.1.4",
  "Authors@R": "person(\"James\", \"Curran\", , \"j.curran@auckland.ac.nz\", role = c(\"aut\", \"cre\"))",
  "Description": "Fits probability models to P- and S-type count data\narising from forensic surveys of clothing for the background\npresence of glass, paint, and related trace material. Built-in\nmodels include zeta, zero-inflated zeta, and logarithmic\ndistributions, with a public extension interface for additional\nmodels. Inference is available by maximum likelihood,\nparametric Bayesian methods, the ordinary nonparametric\nbootstrap, and Rubin's Bayesian Bootstrap. The clothing-survey\nsetting is described by Coulson, Buckleton, Gummer, and Triggs\n(2001) <doi:10.1016/S1355-0306(01)71847-3>.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RdMacros": "Rdpack",
  "URL": "https://github.com/jmcurran/fitPS",
  "BugReports": "https://github.com/jmcurran/fitPS/issues",
  "VignetteBuilder": "knitr",
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  "Repository": "https://jmcurran.r-universe.dev",
  "Date/Publication": "2026-08-16 22:00:57 UTC",
  "RemoteUrl": "https://github.com/jmcurran/fitps",
  "RemoteRef": "HEAD",
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  "Packaged": {
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    "User": "root"
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  "Author": "James Curran [aut, cre]",
  "Maintainer": "James Curran <j.curran@auckland.ac.nz>",
  "_user": "jmcurran",
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  "_created": "2026-09-22T11:50:06.000Z",
  "_published": "2026-09-22T11:55:26.872Z",
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    "description": "Professor of Statistics at the University of Auckland. Keen cyclist and gamer."
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/fitPS"
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  "_devurl": "https://github.com/jmcurran/fitps",
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  "_assets": [
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    "extra/citation.json",
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  "_realowner": "jmcurran",
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  "_releases": [
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      "version": "0.2",
      "date": "2022-12-01"
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      "date": "2023-01-20"
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  "_exports": [
    "add",
    "bootCI",
    "bootstrapFit",
    "bootstrapProbs",
    "compareSurveys",
    "compareSurveysLRT",
    "createPSData",
    "credint",
    "credInt",
    "DIC",
    "fit",
    "fitdist",
    "fitDist",
    "fitlogdist",
    "fitlogDist",
    "fitLogdist",
    "fitzidist",
    "fitZIdist",
    "fitZIDist",
    "logarithmicModel",
    "makeData",
    "makePrior",
    "makePSData",
    "modelBayesControl",
    "modelFromUnconstrained",
    "modelLogJacobian",
    "modelLogLikelihood",
    "modelLogPrior",
    "modelMleControl",
    "modelObservationData",
    "modelParameterNames",
    "modelProbabilities",
    "modelToUnconstrained",
    "plotPosterior",
    "plotUncertainty",
    "posteriorInflation",
    "posteriorProbs",
    "probfun",
    "psModel",
    "readData",
    "rzeta",
    "rzizeta",
    "rZIzeta",
    "supportedPosteriorEngines",
    "var",
    "zetaModel",
    "zizModel"
  ],
  "_datasets": [
    {
      "name": "Psurveys",
      "title": "Number of Groups of Glass Data",
      "object": "Psurveys",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "Ssurveys",
      "title": "Size of Groups of Glass Data",
      "object": "Ssurveys",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
  ],
  "_help": [
    {
      "page": "equals-.psData",
      "title": "S3 method for objects of class 'psData'",
      "topics": [
        "==.psData"
      ]
    },
    {
      "page": "add",
      "title": "Add data to a psData object",
      "topics": [
        "add"
      ]
    },
    {
      "page": "as.data.frame.psData",
      "title": "Converts an object of class 'psData' to a 'data.frame'",
      "topics": [
        "as.data.frame.psData"
      ]
    },
    {
      "page": "bootCI",
      "title": "Legacy bootstrap confidence intervals or regions",
      "topics": [
        "bootCI",
        "bootCI.default",
        "bootCI.psData",
        "bootCI.psFit"
      ]
    },
    {
      "page": "bootstrapFit",
      "title": "Compute a bootstrap distribution for a fitted fitPS model",
      "topics": [
        "bootstrapFit",
        "bootstrapFit.psFit"
      ]
    },
    {
      "page": "bootstrapProbs",
      "title": "Extract bootstrap probability summaries",
      "topics": [
        "bootstrapProbs",
        "bootstrapProbs.psBootstrap",
        "bootstrapProbs.psFit"
      ]
    },
    {
      "page": "compareSurveys",
      "title": "Compare two surveys on the basis of their shape parameters",
      "topics": [
        "comp.survs",
        "compare.surveys",
        "compareSurveys",
        "compareSurveys.default",
        "compareSurveys.psData",
        "compareSurveys.psFit"
      ]
    },
    {
      "page": "compareSurveysLRT",
      "title": "Compare two or more surveys on the basis of their shape parameters using a Likelihood Ratio Test",
      "topics": [
        "compareSurveysLRT"
      ]
    },
    {
      "page": "confint.psFit",
      "title": "S3 confint method for objects of class psFit",
      "topics": [
        "confint.psFit"
      ]
    },
    {
      "page": "credint",
      "title": "Bayesian credible intervals or regions",
      "topics": [
        "credInt",
        "credint"
      ]
    },
    {
      "page": "deviance.psFit",
      "title": "Extract deviance from a fitted fitPS model",
      "topics": [
        "deviance.psFit"
      ]
    },
    {
      "page": "DIC",
      "title": "Compute the deviance information criterion for a Bayesian fitPS model",
      "topics": [
        "DIC"
      ]
    },
    {
      "page": "fit",
      "title": "Fit a fitPS model",
      "topics": [
        "fit"
      ]
    },
    {
      "page": "fitDist",
      "title": "Fit a Zeta Distribution to Forensic Data",
      "topics": [
        "fitDist",
        "fitdist"
      ]
    },
    {
      "page": "fitlogDist",
      "title": "Fit a logarithmic distribution to forensic data",
      "topics": [
        "fitLogdist",
        "fitlogDist",
        "fitlogdist"
      ]
    },
    {
      "page": "fitted.psFit",
      "title": "S3 fitted method for an object of class 'psFit'",
      "topics": [
        "fitted.psFit"
      ]
    },
    {
      "page": "fitted.psPosterior",
      "title": "Extract posterior mean probabilities",
      "topics": [
        "fitted.psPosterior"
      ]
    },
    {
      "page": "fitZIDist",
      "title": "Fit a Zero-Inflated Zeta Distribution to Forensic Data",
      "topics": [
        "fitZIDist",
        "fitZIdist",
        "fitzidist"
      ]
    },
    {
      "page": "zetaModel",
      "title": "Construct built-in fitPS model descriptors",
      "topics": [
        "logarithmicModel",
        "zetaModel",
        "zizModel"
      ]
    },
    {
      "page": "logLik.psFit",
      "title": "Extract the maximised log-likelihood from a fitPS model fit",
      "topics": [
        "logLik.psFit"
      ]
    },
    {
      "page": "makePrior",
      "title": "Define a prior density",
      "topics": [
        "makePrior"
      ]
    },
    {
      "page": "makePSData",
      "title": "Create a survey data set manually",
      "topics": [
        "createPSData",
        "makeData",
        "makePSData"
      ]
    },
    {
      "page": "mean.psData",
      "title": "An S3 method for computing the mean of clothing survey for the number of groups or size of groups",
      "topics": [
        "mean.psData"
      ]
    },
    {
      "page": "modelBayesControl",
      "title": "Return Bayesian fitting controls supplied by a model",
      "topics": [
        "modelBayesControl",
        "modelBayesControl.logarithmicModel",
        "modelBayesControl.psModel",
        "modelBayesControl.zetaModel",
        "modelBayesControl.zizModel"
      ]
    },
    {
      "page": "modelFromUnconstrained",
      "title": "Transform unconstrained coordinates to natural model parameters",
      "topics": [
        "modelFromUnconstrained",
        "modelFromUnconstrained.logarithmicModel",
        "modelFromUnconstrained.psModel",
        "modelFromUnconstrained.zetaModel",
        "modelFromUnconstrained.zizModel"
      ]
    },
    {
      "page": "modelLogJacobian",
      "title": "Evaluate the log-Jacobian for the unconstrained parameter transformation",
      "topics": [
        "modelLogJacobian",
        "modelLogJacobian.logarithmicModel",
        "modelLogJacobian.psModel",
        "modelLogJacobian.zetaModel",
        "modelLogJacobian.zizModel"
      ]
    },
    {
      "page": "modelLogLikelihood",
      "title": "Evaluate a model log likelihood through the shared model protocol.",
      "topics": [
        "modelLogLikelihood"
      ]
    },
    {
      "page": "modelLogPrior",
      "title": "Evaluate a model prior on the natural parameter scale",
      "topics": [
        "modelLogPrior",
        "modelLogPrior.logarithmicModel",
        "modelLogPrior.psModel",
        "modelLogPrior.zetaModel",
        "modelLogPrior.zizModel"
      ]
    },
    {
      "page": "modelMleControl",
      "title": "Return generic maximum-likelihood controls for a model",
      "topics": [
        "modelMleControl",
        "modelMleControl.psModel"
      ]
    },
    {
      "page": "modelObservationData",
      "title": "Convert fitPS data to the observation support required by a model.",
      "topics": [
        "modelObservationData"
      ]
    },
    {
      "page": "modelParameterNames",
      "title": "Return the natural parameter names declared by a fitPS model.",
      "topics": [
        "modelParameterNames"
      ]
    },
    {
      "page": "modelProbabilities",
      "title": "Evaluate fitted P/S probabilities through a model descriptor.",
      "topics": [
        "modelProbabilities"
      ]
    },
    {
      "page": "modelToUnconstrained",
      "title": "Transform natural model parameters to unconstrained coordinates",
      "topics": [
        "modelToUnconstrained",
        "modelToUnconstrained.logarithmicModel",
        "modelToUnconstrained.psModel",
        "modelToUnconstrained.zetaModel",
        "modelToUnconstrained.zizModel"
      ]
    },
    {
      "page": "plot.psBootstrap",
      "title": "Plot bootstrap probability summaries",
      "topics": [
        "plot.psBootstrap"
      ]
    },
    {
      "page": "plot.psFit",
      "title": "S3 plot method for an object of class 'psFit'",
      "topics": [
        "plot.psFit"
      ]
    },
    {
      "page": "plot.psPosterior",
      "title": "Plot posterior probability summaries",
      "topics": [
        "plot.psPosterior"
      ]
    },
    {
      "page": "plotPosterior",
      "title": "Plot a posterior density for a fitted power-series model",
      "topics": [
        "plotPosterior"
      ]
    },
    {
      "page": "plotUncertainty",
      "title": "Plot parameter uncertainty for a fitPS inferential result",
      "topics": [
        "plotUncertainty",
        "plotUncertainty.psBayesianBootstrap",
        "plotUncertainty.psBootstrap",
        "plotUncertainty.psFit"
      ]
    },
    {
      "page": "posteriorInflation",
      "title": "Posterior probability of practically negligible inflation",
      "topics": [
        "posteriorInflation",
        "posteriorInflation.psFit",
        "posteriorInflation.psPosterior"
      ]
    },
    {
      "page": "posteriorProbs",
      "title": "Extract posterior probability summaries",
      "topics": [
        "posteriorProbs",
        "posteriorProbs.psFit",
        "posteriorProbs.psPosterior"
      ]
    },
    {
      "page": "predict.psFit",
      "title": "S3 predict method for an object of class 'psFit'",
      "topics": [
        "predict.psFit"
      ]
    },
    {
      "page": "print.psBayesianBootstrap",
      "title": "Print a fitPS Bayesian Bootstrap object",
      "topics": [
        "print.psBayesianBootstrap"
      ]
    },
    {
      "page": "print.psBootstrap",
      "title": "Print a fitPS bootstrap object",
      "topics": [
        "print.psBootstrap"
      ]
    },
    {
      "page": "print.psData",
      "title": "S3 print method for an object of class 'psData'",
      "topics": [
        "print.psData"
      ]
    },
    {
      "page": "print.psFit",
      "title": "S3 print method for an object of class 'psFit'",
      "topics": [
        "print.psFit"
      ]
    },
    {
      "page": "print.psPosterior",
      "title": "Print a fitPS posterior object",
      "topics": [
        "print.psPosterior"
      ]
    },
    {
      "page": "probfun",
      "title": "Plug-in probability functions",
      "topics": [
        "probfun"
      ]
    },
    {
      "page": "psModel",
      "title": "Construct a public fitPS model descriptor",
      "topics": [
        "psModel"
      ]
    },
    {
      "page": "Psurveys",
      "title": "Number of Groups of Glass Data",
      "topics": [
        "Psurveys"
      ]
    },
    {
      "page": "readData",
      "title": "Read count data from file",
      "topics": [
        "readData"
      ]
    },
    {
      "page": "rzeta",
      "title": "Generate random variates from a zeta distribution",
      "topics": [
        "rzeta"
      ]
    },
    {
      "page": "rZIzeta",
      "title": "Generate zero inflated zeta random variates",
      "topics": [
        "rZIzeta",
        "rzizeta"
      ]
    },
    {
      "page": "Ssurveys",
      "title": "Size of Groups of Glass Data",
      "topics": [
        "Ssurveys"
      ]
    },
    {
      "page": "summary.psBayesianBootstrap",
      "title": "Summarise a fitPS Bayesian Bootstrap object",
      "topics": [
        "print.summary.psBayesianBootstrap",
        "summary.psBayesianBootstrap"
      ]
    },
    {
      "page": "summary.psBootstrap",
      "title": "Summarise a fitPS bootstrap object",
      "topics": [
        "print.summary.psBootstrap",
        "summary.psBootstrap"
      ]
    },
    {
      "page": "summary.psFit",
      "title": "S3 summary method for an object of class 'psFit'",
      "topics": [
        "summary.psFit"
      ]
    },
    {
      "page": "summary.psPosterior",
      "title": "Summarise a fitPS posterior object",
      "topics": [
        "print.summary.psPosterior",
        "summary.psPosterior"
      ]
    },
    {
      "page": "supportedPosteriorEngines",
      "title": "Return posterior engines supported by a fitPS model.",
      "topics": [
        "supportedPosteriorEngines"
      ]
    },
    {
      "page": "var",
      "title": "Variance generic",
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        "Fitting a zeta distribution",
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        "References"
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        "Two kinds of uncertainty",
        "Four approaches available in fitPS",
        "Fit the ZIZ model",
        "Confidence and credible regions for the parameters",
        "Comparing parameter uncertainty across the four methods",
        "From parameter uncertainty to probability uncertainty",
        "Comparing the probability estimates",
        "What does the inflation parameter mean?",
        "Which method should I use?",
        "References"
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