{
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  "Title": "Density and Abundance from Distance-Sampling Surveys",
  "Version": "4.5.0",
  "Date": "2026-09-17",
  "Language": "en-US",
  "Maintainer": "Trent McDonald <trent@mcdonalddatasciences.com>",
  "Authors@R": "c(person(\"Trent\", \"McDonald\", role=c(\"cre\",\"aut\"), email=\"trent@mcdonalddatasciences.com\"), \nperson(\"Jason\", \"Carlisle\", role=\"aut\", email=\"jason.carlisle@wyo.gov\"),\nperson(\"Aidan\", \"McDonald\", role=\"aut\", email=\"aidan@mcdcentral.org\", comment=\"point transect methods\"),\nperson(\"Ryan\", \"Nielson\", role=\"ctb\", comment=\"smoothed likelihood\"),\nperson(\"Ben\", \"Augustine\", role=\"ctb\", comment=\"maximization method\"),\nperson(\"James\", \"Griswald\", role=\"ctb\", comment=\"maximization method\"),\nperson(\"Patrick\", \"McKann\", role=\"ctb\", comment=\"maximization method\"),\nperson(\"Lacey\", \"Jeroue\", role=\"ctb\", comment=\"vignettes\"),\nperson(\"Hoffman\", \"Abigail\", role=\"ctb\", comment=\"vignettes\"),\nperson(\"Kleinsausser\", \"Michael\", role=\"ctb\", comment=\"vignettes\"),\nperson(\"Joel\", \"Reynolds\", role=\"ctb\", comment=\"Gamma likelihood\"),\nperson(\"Pham\", \"Quang\", role=\"ctb\", comment=\"Gamma likelihood\"),\nperson(\"Earl\", \"Becker\", role=\"ctb\", comment=\"Gamma likelihood\"),\nperson(\"Aaron\", \"Christ\", role=\"ctb\", comment=\"Gamma likelihood\"),\nperson(\"Brook\", \"Russelland\", role=\"ctb\", comment=\"Gamma likelihood\"),\nperson(\"Stefan\", \"Emmons\", role=\"ctb\", comment=\"Automated tests\"),\nperson(\"Will\", \"McDonald\", role=\"ctb\", comment=\"Automated tests\"),\nperson(\"Reid\", \"Olson\", role=\"ctb\", comment=\"Automated tests and bug fixes\"))",
  "Description": "Distance-sampling (<doi:10.1007/978-3-319-19219-2>) is a\nfield survey and analytical method that estimates density and\nabundance of survey targets (e.g., animals) when detection\nprobability declines with observation distance.\nDistance-sampling is popular in ecology, especially when survey\ntargets are observed from aerial platforms (e.g., airplane or\ndrone), surface vessels (e.g., boat or truck), or along walking\ntransects. Analysis involves fitting smooth (parametric) curves\nto histograms of observation distances and using those\nfunctions to adjust density estimates for missed targets.\nRoutines included here fit curves to observation distance\nhistograms, estimate effective sampling area, density of\ntargets in surveyed areas, and the abundance of targets in a\nsurrounding study area. Confidence interval estimation uses\nbuilt-in bootstrap resampling. Help files are extensive and\nhave been vetted by multiple authors. Many tutorials are\navailable on the package's website (URL below).",
  "License": "GNU General Public License",
  "URL": "https://mcdonalddatasciences.com/Rdistance.html",
  "BugReports": "https://github.com/tmcd82070/Rdistance/issues",
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  "Repository": "https://tmcd82070.r-universe.dev",
  "Date/Publication": "2026-09-18 00:50:01 UTC",
  "RemoteUrl": "https://github.com/tmcd82070/rdistance",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-10-18 06:24:33 UTC",
    "User": "root"
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  "Author": "Trent McDonald [cre, aut],\nJason Carlisle [aut],\nAidan McDonald [aut] (point transect methods),\nRyan Nielson [ctb] (smoothed likelihood),\nBen Augustine [ctb] (maximization method),\nJames Griswald [ctb] (maximization method),\nPatrick McKann [ctb] (maximization method),\nLacey Jeroue [ctb] (vignettes),\nHoffman Abigail [ctb] (vignettes),\nKleinsausser Michael [ctb] (vignettes),\nJoel Reynolds [ctb] (Gamma likelihood),\nPham Quang [ctb] (Gamma likelihood),\nEarl Becker [ctb] (Gamma likelihood),\nAaron Christ [ctb] (Gamma likelihood),\nBrook Russelland [ctb] (Gamma likelihood),\nStefan Emmons [ctb] (Automated tests),\nWill McDonald [ctb] (Automated tests),\nReid Olson [ctb] (Automated tests and bug fixes)",
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  "_created": "2026-10-18T06:24:33.000Z",
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    "%#%",
    "%acre%",
    "%cm%",
    "%ft%",
    "%ha%",
    "%inches%",
    "%km%",
    "%km^2%",
    "%m%",
    "%m^2%",
    "%mi%",
    "%mi^2%",
    "%yd%",
    "abundEstim",
    "autoDistSamp",
    "bcCI",
    "bootstrap",
    "bspline.expansion",
    "calcLineLength",
    "checkUnits",
    "convexPartition",
    "cosine.expansion",
    "dE.multi",
    "dE.single",
    "dfuncEstim",
    "differentiableLikelihoods",
    "distances",
    "drawTransects",
    "dropUnits",
    "EDR",
    "effectiveDistance",
    "effort",
    "estimateN",
    "ESW",
    "expandW",
    "expansionTerms",
    "findSpacing",
    "Gamma.like",
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    "GammaModes",
    "GammaReparam",
    "groupSizes",
    "gxEstim",
    "halfnorm.like",
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    "hazrate.start.limits",
    "hermite.expansion",
    "huber.cumFunc",
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    "huber.start.limits",
    "integrateDfuncs",
    "integrateGammaLines",
    "integrateHalfnormLines",
    "integrateHalfnormPoints",
    "integrateHazrateLines",
    "integrateHuberLines",
    "integrateNegexpLines",
    "integrateNegexpPoints",
    "integrateNumeric",
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    "nLL",
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    "oneStep.like",
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    "parseModel",
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    "unnest",
    "varcovarEstim"
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      "name": "exampleSurveyPoly",
      "title": "Example complex survey polygons",
      "object": "exampleSurveyPoly",
      "class": [
        "sf",
        "data.frame"
      ],
      "fields": [
        "geometry"
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      "table": false,
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        "tbl",
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        "detections"
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      "tojson": false
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      "object": "sparrowDf",
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    {
      "page": "Rdistance-package",
      "title": "Rdistance - Distance Sampling Analyses for Abundance Estimation",
      "topics": [
        "Rdistance-package",
        "distance",
        "line-transect",
        "point-transect",
        "Rdistance"
      ]
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      "title": "Unit assignment helpers",
      "topics": [
        "%#%",
        "%acre%",
        "%cm%",
        "%ft%",
        "%ha%",
        "%inches%",
        "%km%",
        "%km^2%",
        "%m%",
        "%mi%",
        "%mi^2%",
        "%m^2%",
        "%yd%",
        "dropUnits",
        "setUnits",
        "unitHelpers"
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    {
      "page": "abundEstim",
      "title": "Distance Sampling Abundance Estimates",
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      ]
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    {
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      "title": "AIC-related fit statistics for detection functions",
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      "topics": [
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        "bootstrap"
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      "title": "B-spline expansion terms",
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      ]
    },
    {
      "page": "calcLineLength",
      "title": "Calculate target transect length",
      "topics": [
        "calcLineLength"
      ]
    },
    {
      "page": "checkNEvalPts",
      "title": "Check number of numeric integration intervals",
      "topics": [
        "checkNEvalPts"
      ]
    },
    {
      "page": "checkUnits",
      "title": "Check for the presence of units",
      "topics": [
        "checkUnits"
      ]
    },
    {
      "page": "coef.dfunc",
      "title": "Coefficients of an estimated detection function",
      "topics": [
        "coef.dfunc"
      ]
    },
    {
      "page": "colorize",
      "title": "Add color to result if terminal accepts it",
      "topics": [
        "colorize"
      ]
    },
    {
      "page": "convexPartition",
      "title": "Partition a concave polygon into more-convex pieces",
      "topics": [
        "convexPartition"
      ]
    },
    {
      "page": "cosine.expansion",
      "title": "Cosine expansion terms",
      "topics": [
        "cosine.expansion"
      ]
    },
    {
      "page": "dE.multi",
      "title": "Estimate multiple-observer line-transect distance functions",
      "topics": [
        "dE.multi"
      ]
    },
    {
      "page": "dE.single",
      "title": "Estimate single-observer line-transect distance function",
      "topics": [
        "dE.single"
      ]
    },
    {
      "page": "dfuncEstim",
      "title": "Estimate a distance-based detection function",
      "topics": [
        "dfuncEstim"
      ]
    },
    {
      "page": "dfuncEstimErrMessage",
      "title": "dfuncEstim error messages",
      "topics": [
        "dfuncEstimErrMessage"
      ]
    },
    {
      "page": "differentiableLikelihoods",
      "title": "Differentiable likelihoods in Rdistance",
      "topics": [
        "differentiableLikelihoods"
      ]
    },
    {
      "page": "distances",
      "title": "Observation distances",
      "topics": [
        "distances"
      ]
    },
    {
      "page": "drawTransects",
      "title": "Draw random transects given target length",
      "topics": [
        "drawTransects"
      ]
    },
    {
      "page": "EDR",
      "title": "Effective Detection Radius (EDR) for point transects",
      "topics": [
        "EDR"
      ]
    },
    {
      "page": "effectiveDistance",
      "title": "Effective sampling distances",
      "topics": [
        "effectiveDistance"
      ]
    },
    {
      "page": "effort",
      "title": "Effort information",
      "topics": [
        "effort"
      ]
    },
    {
      "page": "errDataUnk",
      "title": "Unknown error message",
      "topics": [
        "errDataUnk"
      ]
    },
    {
      "page": "estimateN",
      "title": "Abundance point estimates",
      "topics": [
        "estimateN"
      ]
    },
    {
      "page": "ESW",
      "title": "Effective Strip Width (ESW) for line transects",
      "topics": [
        "ESW"
      ]
    },
    {
      "page": "exampleSurveyPoly",
      "title": "Example complex survey polygons",
      "topics": [
        "exampleSurveyPoly"
      ]
    },
    {
      "page": "expandW",
      "title": "Domain of expansion factors",
      "topics": [
        "expandW"
      ]
    },
    {
      "page": "expansionTerms",
      "title": "Distance function expansion terms",
      "topics": [
        "expansionTerms"
      ]
    },
    {
      "page": "findSpacing",
      "title": "findSpacing - Transect spacing for a target survey length",
      "topics": [
        "findSpacing"
      ]
    },
    {
      "page": "Gamma.like",
      "title": "Gamma distance function",
      "topics": [
        "Gamma.like"
      ]
    },
    {
      "page": "Gamma.start.limits",
      "title": "Gamma.start.limits - Start and limit values for Gamma distance function",
      "topics": [
        "Gamma.start.limits"
      ]
    },
    {
      "page": "GammaModes",
      "title": "Modes of the Gamma distribution",
      "topics": [
        "GammaModes"
      ]
    },
    {
      "page": "GammaReparam",
      "title": "Reparameterize Gamma parameters for use in dgamma",
      "topics": [
        "GammaReparam"
      ]
    },
    {
      "page": "getNCores",
      "title": "Set number of cores",
      "topics": [
        "getNCores"
      ]
    },
    {
      "page": "groupSizes",
      "title": "Group Sizes",
      "topics": [
        "groupSizes"
      ]
    },
    {
      "page": "gxEstim",
      "title": "Estimate g(0) or g(x)",
      "topics": [
        "gxEstim"
      ]
    },
    {
      "page": "halfnorm.like",
      "title": "Half-normal distance function",
      "topics": [
        "halfnorm.like"
      ]
    },
    {
      "page": "halfnorm.start.limits",
      "title": "Start and limit values for halfnorm distance function",
      "topics": [
        "halfnorm.start.limits"
      ]
    },
    {
      "page": "hazrate.like",
      "title": "Hazard rate likelihood",
      "topics": [
        "hazrate.like"
      ]
    },
    {
      "page": "hazrate.start.limits",
      "title": "Start and limit values for hazrate distance function",
      "topics": [
        "hazrate.start.limits"
      ]
    },
    {
      "page": "hermite.expansion",
      "title": "Hermite expansion factors",
      "topics": [
        "hermite.expansion"
      ]
    },
    {
      "page": "HookeJeeves",
      "title": "'nlminb' optimizer",
      "topics": [
        "HookeJeeves"
      ]
    },
    {
      "page": "huber.cumFunc",
      "title": "Huber Cumulative Function",
      "topics": [
        "huber.cumFunc"
      ]
    },
    {
      "page": "huber.like",
      "title": "Huber distance function",
      "topics": [
        "huber.like"
      ]
    },
    {
      "page": "huber.start.limits",
      "title": "Start and limit values for the Huber distance function",
      "topics": [
        "huber.start.limits"
      ]
    },
    {
      "page": "insertOneStepBreaks",
      "title": "Insert oneStep Likelihood breaks",
      "topics": [
        "insertOneStepBreaks"
      ]
    },
    {
      "page": "integrateDfuncs",
      "title": "Integration of distance functions",
      "topics": [
        "integrateDfuncs"
      ]
    },
    {
      "page": "integrateGammaLines",
      "title": "Integrate Gamma line surveys",
      "topics": [
        "integrateGammaLines"
      ]
    },
    {
      "page": "integrateHalfnormLines",
      "title": "Integrate Half-normal line surveys",
      "topics": [
        "integrateHalfnormLines"
      ]
    },
    {
      "page": "integrateHalfnormPoints",
      "title": "Integrate Half-normal Point transects",
      "topics": [
        "integrateHalfnormPoints"
      ]
    },
    {
      "page": "integrateHazrateLines",
      "title": "Integrate Hazard-rate line survey distance functions",
      "topics": [
        "integrateHazrateLines"
      ]
    },
    {
      "page": "integrateHuberLines",
      "title": "Integrate Line-transect Huber function",
      "topics": [
        "integrateHuberLines"
      ]
    },
    {
      "page": "integrateKey",
      "title": "Compute and print distance function integration",
      "topics": [
        "integrateKey"
      ]
    },
    {
      "page": "integrateNegexpLines",
      "title": "Integrate Negative exponential",
      "topics": [
        "integrateNegexpLines"
      ]
    },
    {
      "page": "integrateNegexpPoints",
      "title": "Integrate Negative exponential point surveys",
      "topics": [
        "integrateNegexpPoints"
      ]
    },
    {
      "page": "integrateNumeric",
      "title": "Numeric Integration",
      "topics": [
        "integrateNumeric"
      ]
    },
    {
      "page": "integrateOneStepLines",
      "title": "Integrate Line-transect One-step function",
      "topics": [
        "integrateOneStepLines"
      ]
    },
    {
      "page": "integrateOneStepNumeric",
      "title": "Numeric Integration of One-step Function",
      "topics": [
        "integrateOneStepNumeric"
      ]
    },
    {
      "page": "integrateOneStepPoints",
      "title": "Integrate Point-survey One-step function",
      "topics": [
        "integrateOneStepPoints"
      ]
    },
    {
      "page": "integrateTriangleLines",
      "title": "Integrate Line-transect Triangle function",
      "topics": [
        "integrateTriangleLines"
      ]
    },
    {
      "page": "intercept.only",
      "title": "Detect intercept-only distance function",
      "topics": [
        "intercept.only"
      ]
    },
    {
      "page": "is.points",
      "title": "Tests for point surveys",
      "topics": [
        "is.points"
      ]
    },
    {
      "page": "is.RdistDf",
      "title": "Check RdistDf data frames",
      "topics": [
        "is.RdistDf"
      ]
    },
    {
      "page": "is.smoothed",
      "title": "Tests for smoothed distance functions",
      "topics": [
        "is.smoothed"
      ]
    },
    {
      "page": "is.Unitless",
      "title": "Test whether object is unitless",
      "topics": [
        "is.Unitless"
      ]
    },
    {
      "page": "likeParamNames",
      "title": "Likelihood parameter names",
      "topics": [
        "likeParamNames"
      ]
    },
    {
      "page": "lines.dfunc",
      "title": "lines.dfunc - Line plotting method for distance functions",
      "topics": [
        "lines.dfunc"
      ]
    },
    {
      "page": "makeLines",
      "title": "makeLines - Place random transects at a given spacing",
      "topics": [
        "makeLines"
      ]
    },
    {
      "page": "maximize.g",
      "title": "Find coordinate of function maximum",
      "topics": [
        "maximize.g"
      ]
    },
    {
      "page": "mlEstimates",
      "title": "Distance function maximum likelihood estimates",
      "topics": [
        "mlEstimates"
      ]
    },
    {
      "page": "model.matrix.dfunc",
      "title": "Rdistance model matrix",
      "topics": [
        "model.matrix.dfunc"
      ]
    },
    {
      "page": "nCovars",
      "title": "Number of covariates",
      "topics": [
        "nCovars"
      ]
    },
    {
      "page": "negexp.like",
      "title": "Negative exponential likelihood",
      "topics": [
        "negexp.like"
      ]
    },
    {
      "page": "negexp.start.limits",
      "title": "Start and limit values for negexp distance function",
      "topics": [
        "negexp.start.limits"
      ]
    },
    {
      "page": "nLL",
      "title": "Negative log likelihood of distances",
      "topics": [
        "nLL"
      ]
    },
    {
      "page": "Nlminb",
      "title": "'nlminb' optimizer",
      "topics": [
        "Nlminb"
      ]
    },
    {
      "page": "observationType",
      "title": "Type of observations",
      "topics": [
        "observationType"
      ]
    },
    {
      "page": "oneBsIter",
      "title": "Calculations for one bootstrap iteration",
      "topics": [
        "oneBsIter"
      ]
    },
    {
      "page": "oneStep.like",
      "title": "Mixture of two uniforms likelihood",
      "topics": [
        "oneStep.like"
      ]
    },
    {
      "page": "oneStep.start.limits",
      "title": "oneStep likelihood start and limit values",
      "topics": [
        "oneStep.start.limits"
      ]
    },
    {
      "page": "Optim",
      "title": "'optim' optimizer",
      "topics": [
        "Optim"
      ]
    },
    {
      "page": "Oscars",
      "title": "OSCARS optimizer",
      "topics": [
        "Oscars"
      ]
    },
    {
      "page": "oscarsLimits",
      "title": "Modify start and limits for OSCARS optimization",
      "topics": [
        "oscarsLimits"
      ]
    },
    {
      "page": "parseModel",
      "title": "Parse Rdistance model",
      "topics": [
        "parseModel"
      ]
    },
    {
      "page": "perpDists",
      "title": "Compute off-transect distances from sighting distances and angles",
      "topics": [
        "perpDists"
      ]
    },
    {
      "page": "plot.dfunc",
      "title": "Plot method for distance (detection) functions",
      "topics": [
        "plot.dfunc"
      ]
    },
    {
      "page": "plot.dfunc.para",
      "title": "Plot parametric distance functions",
      "topics": [
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      "page": "predDensity",
      "title": "Density on transects",
      "topics": [
        "predDensity"
      ]
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    {
      "page": "predDfuncs",
      "title": "Predict distance functions",
      "topics": [
        "predDfuncs"
      ]
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    {
      "page": "predict.dfunc",
      "title": "Predict distance functions",
      "topics": [
        "predict.dfunc"
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    },
    {
      "page": "predLikelihood",
      "title": "Distance function values at observations",
      "topics": [
        "predLikelihood"
      ]
    },
    {
      "page": "print.abund",
      "title": "Print abundance estimates",
      "topics": [
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    },
    {
      "page": "print.dfunc",
      "title": "Print method for distance function object",
      "topics": [
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    },
    {
      "page": "pronghornDf",
      "title": "Pronghorn Line Transect Data",
      "topics": [
        "pronghornAreas",
        "pronghornDf"
      ]
    },
    {
      "page": "RdistanceControls",
      "title": "Rdistance optimization control parameters.",
      "concept": [
        "control optimization"
      ],
      "topics": [
        "control",
        "controls",
        "RdistanceControls"
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      "page": "RdistDf",
      "title": "Construct Rdistance nested data frames",
      "topics": [
        "RdistDf"
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      "page": "secondDeriv",
      "title": "Numeric second derivatives",
      "topics": [
        "secondDeriv"
      ]
    },
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      "page": "setOptimizer",
      "title": "Set optimizing routine",
      "topics": [
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      "page": "simple.expansion",
      "title": "Simple polynomial expansion factors",
      "topics": [
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    {
      "page": "simpsonCoefs",
      "title": "Simpson numerical integration coefficients",
      "topics": [
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      "page": "sine.expansion",
      "title": "Sine expansion terms",
      "topics": [
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      "page": "sparrowDetectionData",
      "title": "Brewer's Sparrow detection data",
      "topics": [
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      "page": "sparrowDf",
      "title": "Brewer's Sparrow detection data frame in Rdistance >4.0.0 format.",
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      "page": "sparrowDfuncObserver",
      "title": "Brewer's Sparrow detection function",
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      "page": "sparrowSiteData",
      "title": "Brewer's Sparrow site data",
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      "page": "startLimits",
      "title": "Distance function starting values and limits",
      "topics": [
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      "title": "Summarize abundance estimates",
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      "title": "Summary method for Rdistance data frames",
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      "title": "Unnest an RdistDf data frame",
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