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  "Package": "phenesse",
  "Title": "Estimate Phenological Metrics using Presence-Only Data",
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  "Authors@R": "c(person(\"Michael\", \"Belitz\", email = \"michaelbelitz06@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-8162-5998\")),\nperson(\"Caitlin\", \"Campbell\", email = \"caitjcampbell@gmail.com\", role = \"ctb\", comment = c(ORCID = \"0000-0002-8199-7775\")),\nperson(\"Daijiang\", \"Li\", email = \"daijianglee@gmail.com\", role = \"ctb\", comment = c(ORCID = \"0000-0002-0925-3421\")))",
  "Description": "Generates Weibull-parameterized estimates of phenology for\nany percentile of a distribution using the framework\nestablished in Cooke (1979) <doi:10.1093/biomet/66.2.367>.\nExtensive testing against other estimators suggest the\nweib_percentile() function is especially useful in generating\nmore accurate and less biased estimates of onset and offset\n(Belitz et al. 2020) <doi:10.1111/2041-210X.13448>.\nNon-parametric bootstrapping can be used to generate confidence\nintervals around those estimates, although this is\ncomputationally expensive. Additionally, this package offers an\neasy way to perform non-parametric bootstrapping to generate\nconfidence intervals for quantile estimates, mean estimates, or\nany statistical function of interest.",
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  "License": "CC0",
  "URL": "https://github.com/mbelitz/phenesse",
  "BugReports": "https://github.com/mbelitz/phenesse/issues",
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  "Date/Publication": "2025-06-11 15:27:43 UTC",
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  "Author": "Michael Belitz [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-8162-5998>),\nCaitlin Campbell [ctb] (ORCID: <https://orcid.org/0000-0002-8199-7775>),\nDaijiang Li [ctb] (ORCID: <https://orcid.org/0000-0002-0925-3421>)",
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      "date": "2019-12-22"
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    },
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      "date": "2020-07-29"
    },
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      "date": "2025-06-10"
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    "mean_ci",
    "quantile_ci",
    "weib_percentile",
    "weib_percentile_ci"
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      "title": "Example iNaturalist-sourced data",
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        "latitude",
        "longitude",
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        "doy"
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    {
      "page": "estimate_ci",
      "title": "Calculate confidence intervals using bootstrap of any statistical function of interest.",
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        "estimate_ci"
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    {
      "page": "inat_examples",
      "title": "Example iNaturalist-sourced data",
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        "inat_examples"
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    {
      "page": "mean_ci",
      "title": "Calculating the confidence intervals (CIs) of an arithmetic mean.",
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    },
    {
      "page": "quantile_ci",
      "title": "Calculating the confidence intervals (CIs) of a quantile estimate of a a vector of observations using non-parametric bootstrapping.",
      "topics": [
        "quantile_ci"
      ]
    },
    {
      "page": "weib_percentile",
      "title": "Calculating a percentile estimate of a seasonal abundance distribution from incidental observations.",
      "topics": [
        "weib_percentile"
      ]
    },
    {
      "page": "weib_percentile_ci",
      "title": "Calculating the CIs of a percentile estimate of a seasonal abundance distribution using the non-parametric bootstrapping.",
      "topics": [
        "weib_percentile_ci"
      ]
    }
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    "fitdistrplus",
    "lattice",
    "MASS",
    "Matrix",
    "rlang",
    "survival"
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      "filename": "phenesse_vignette.html",
      "title": "phenesse vignette",
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      "headings": [
        "Overview",
        "Loading example data",
        "The main function of 'phenesse': weib_percentile",
        "weib_percentile calculates a Weibull-parameterized estimate of phenology for any percentile of a distribution",
        "Use non-parametric bootstrapping to calculate confidence interval of estimate",
        "CAUTION: Calculating confidence interval of Weibull-corrected estimates are computationally expensive. Consider options to parallelize calculations",
        "Options to parallelize weib_percentile_ci",
        "CIs for mean and quantile estimates",
        "Another functionality of phenesse, is it provides functions to calculate confidence intervals of quantile and mean estimates using non-parametric bootstrapping"
      ],
      "created": "2019-11-07 18:50:25",
      "modified": "2020-07-28 14:50:10",
      "commits": 8
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