{
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  "Package": "distributional",
  "Title": "Vectorised Probability Distributions",
  "Version": "0.7.0.9000",
  "Authors@R": "c(person(given = \"Mitchell\",\nfamily = \"O'Hara-Wild\",\nrole = c(\"aut\", \"cre\"),\nemail = \"mail@mitchelloharawild.com\",\ncomment = c(ORCID = \"0000-0001-6729-7695\")),\nperson(given = \"Matthew\",\nfamily = \"Kay\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-9446-0419\")),\nperson(given = \"Alex\",\nfamily = \"Hayes\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-4985-5160\")),\nperson(given = \"Rob\",\nfamily = \"Hyndman\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-2140-5352\")),\nperson(given = \"Earo\",\nfamily = \"Wang\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0001-6448-5260\")),\nperson(given = \"Vencislav\",\nfamily = \"Popov\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-8073-4199\")))",
  "Description": "Vectorised distribution objects with tools for\nmanipulating, visualising, and using probability distributions.\nDesigned to allow model prediction outputs to return\ndistributions rather than their parameters, allowing users to\ndirectly interact with predictive distributions in a\ndata-oriented workflow. In addition to providing generic\nreplacements for p/d/q/r functions, other useful statistics can\nbe computed including means, variances, intervals, and highest\ndensity regions.",
  "License": "GPL-3",
  "RdMacros": "lifecycle",
  "URL": "https://pkg.mitchelloharawild.com/distributional/,\nhttps://github.com/mitchelloharawild/distributional",
  "BugReports": "https://github.com/mitchelloharawild/distributional/issues",
  "Encoding": "UTF-8",
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  "Repository": "https://mitchelloharawild.r-universe.dev",
  "Date/Publication": "2026-05-27 12:31:54 UTC",
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  "Author": "Mitchell O'Hara-Wild [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-6729-7695>),\nMatthew Kay [aut] (ORCID: <https://orcid.org/0000-0001-9446-0419>),\nAlex Hayes [aut] (ORCID: <https://orcid.org/0000-0002-4985-5160>),\nRob Hyndman [aut] (ORCID: <https://orcid.org/0000-0002-2140-5352>),\nEaro Wang [ctb] (ORCID: <https://orcid.org/0000-0001-6448-5260>),\nVencislav Popov [ctb] (ORCID: <https://orcid.org/0000-0002-8073-4199>)",
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    "cdf",
    "covariance",
    "dist_bernoulli",
    "dist_beta",
    "dist_binomial",
    "dist_burr",
    "dist_categorical",
    "dist_cauchy",
    "dist_chisq",
    "dist_degenerate",
    "dist_dirichlet",
    "dist_exponential",
    "dist_f",
    "dist_gamma",
    "dist_geometric",
    "dist_gev",
    "dist_gh",
    "dist_gk",
    "dist_gpd",
    "dist_gumbel",
    "dist_horseshoe",
    "dist_hypergeometric",
    "dist_inflated",
    "dist_inverse_exponential",
    "dist_inverse_gamma",
    "dist_inverse_gaussian",
    "dist_laplace",
    "dist_logarithmic",
    "dist_logistic",
    "dist_lognormal",
    "dist_missing",
    "dist_mixture",
    "dist_multinomial",
    "dist_multivariate_normal",
    "dist_multivariate_t",
    "dist_negative_binomial",
    "dist_normal",
    "dist_pareto",
    "dist_percentile",
    "dist_poisson",
    "dist_poisson_inverse_gaussian",
    "dist_sample",
    "dist_student_t",
    "dist_studentized_range",
    "dist_transformed",
    "dist_truncated",
    "dist_uniform",
    "dist_weibull",
    "dist_wrap",
    "generate",
    "has_symmetry",
    "hdr",
    "hilo",
    "is_distribution",
    "is_hdr",
    "is_hilo",
    "kurtosis",
    "likelihood",
    "log_likelihood",
    "new_dist",
    "new_hdr",
    "new_hilo",
    "parameters",
    "skewness",
    "support",
    "variance"
  ],
  "_help": [
    {
      "page": "cdf",
      "title": "The cumulative distribution function",
      "topics": [
        "cdf",
        "cdf.distribution"
      ]
    },
    {
      "page": "covariance",
      "title": "Covariance",
      "topics": [
        "covariance"
      ]
    },
    {
      "page": "covariance.distribution",
      "title": "Covariance of a probability distribution",
      "topics": [
        "covariance.distribution"
      ]
    },
    {
      "page": "density.distribution",
      "title": "The probability density/mass function",
      "topics": [
        "density.distribution"
      ]
    },
    {
      "page": "dist_bernoulli",
      "title": "The Bernoulli distribution",
      "topics": [
        "dist_bernoulli"
      ]
    },
    {
      "page": "dist_beta",
      "title": "The Beta distribution",
      "topics": [
        "dist_beta"
      ]
    },
    {
      "page": "dist_binomial",
      "title": "The Binomial distribution",
      "topics": [
        "dist_binomial"
      ]
    },
    {
      "page": "dist_burr",
      "title": "The Burr distribution",
      "topics": [
        "dist_burr"
      ]
    },
    {
      "page": "dist_categorical",
      "title": "The Categorical distribution",
      "topics": [
        "dist_categorical"
      ]
    },
    {
      "page": "dist_cauchy",
      "title": "The Cauchy distribution",
      "topics": [
        "dist_cauchy"
      ]
    },
    {
      "page": "dist_chisq",
      "title": "The (non-central) Chi-Squared Distribution",
      "topics": [
        "dist_chisq"
      ]
    },
    {
      "page": "dist_degenerate",
      "title": "The degenerate distribution",
      "topics": [
        "dist_degenerate"
      ]
    },
    {
      "page": "dist_dirichlet",
      "title": "The Dirichlet distribution",
      "topics": [
        "dist_dirichlet"
      ]
    },
    {
      "page": "dist_exponential",
      "title": "The Exponential Distribution",
      "topics": [
        "dist_exponential"
      ]
    },
    {
      "page": "dist_f",
      "title": "The F Distribution",
      "topics": [
        "dist_f"
      ]
    },
    {
      "page": "dist_gamma",
      "title": "The Gamma distribution",
      "topics": [
        "dist_gamma"
      ]
    },
    {
      "page": "dist_geometric",
      "title": "The Geometric Distribution",
      "topics": [
        "dist_geometric"
      ]
    },
    {
      "page": "dist_gev",
      "title": "The Generalized Extreme Value Distribution",
      "topics": [
        "dist_gev"
      ]
    },
    {
      "page": "dist_gh",
      "title": "The generalised g-and-h Distribution",
      "topics": [
        "dist_gh"
      ]
    },
    {
      "page": "dist_gk",
      "title": "The g-and-k Distribution",
      "topics": [
        "dist_gk"
      ]
    },
    {
      "page": "dist_gpd",
      "title": "The Generalized Pareto Distribution",
      "topics": [
        "dist_gpd"
      ]
    },
    {
      "page": "dist_gumbel",
      "title": "The Gumbel distribution",
      "topics": [
        "dist_gumbel"
      ]
    },
    {
      "page": "dist_horseshoe",
      "title": "The Horseshoe distribution",
      "topics": [
        "dist_horseshoe"
      ]
    },
    {
      "page": "dist_hypergeometric",
      "title": "The Hypergeometric distribution",
      "topics": [
        "dist_hypergeometric"
      ]
    },
    {
      "page": "dist_inflated",
      "title": "Inflate a value of a probability distribution",
      "topics": [
        "dist_inflated"
      ]
    },
    {
      "page": "dist_inverse_exponential",
      "title": "The Inverse Exponential distribution",
      "topics": [
        "dist_inverse_exponential"
      ]
    },
    {
      "page": "dist_inverse_gamma",
      "title": "The Inverse Gamma distribution",
      "topics": [
        "dist_inverse_gamma"
      ]
    },
    {
      "page": "dist_inverse_gaussian",
      "title": "The Inverse Gaussian distribution",
      "topics": [
        "dist_inverse_gaussian"
      ]
    },
    {
      "page": "dist_laplace",
      "title": "The Laplace distribution",
      "topics": [
        "dist_laplace"
      ]
    },
    {
      "page": "dist_logarithmic",
      "title": "The Logarithmic distribution",
      "topics": [
        "dist_logarithmic"
      ]
    },
    {
      "page": "dist_logistic",
      "title": "The Logistic distribution",
      "topics": [
        "dist_logistic"
      ]
    },
    {
      "page": "dist_lognormal",
      "title": "The log-normal distribution",
      "topics": [
        "dist_lognormal"
      ]
    },
    {
      "page": "dist_missing",
      "title": "Missing distribution",
      "topics": [
        "dist_missing"
      ]
    },
    {
      "page": "dist_mixture",
      "title": "Create a mixture of distributions",
      "topics": [
        "dist_mixture"
      ]
    },
    {
      "page": "dist_multinomial",
      "title": "The Multinomial distribution",
      "topics": [
        "dist_multinomial"
      ]
    },
    {
      "page": "dist_multivariate_normal",
      "title": "The multivariate normal distribution",
      "topics": [
        "dist_multivariate_normal"
      ]
    },
    {
      "page": "dist_multivariate_t",
      "title": "The multivariate t-distribution",
      "topics": [
        "dist_multivariate_t"
      ]
    },
    {
      "page": "dist_negative_binomial",
      "title": "The Negative Binomial distribution",
      "topics": [
        "dist_negative_binomial"
      ]
    },
    {
      "page": "dist_normal",
      "title": "The Normal distribution",
      "topics": [
        "dist_normal"
      ]
    },
    {
      "page": "dist_pareto",
      "title": "The Pareto Distribution",
      "topics": [
        "dist_pareto"
      ]
    },
    {
      "page": "dist_percentile",
      "title": "Percentile distribution",
      "topics": [
        "dist_percentile"
      ]
    },
    {
      "page": "dist_poisson",
      "title": "The Poisson Distribution",
      "topics": [
        "dist_poisson"
      ]
    },
    {
      "page": "dist_poisson_inverse_gaussian",
      "title": "The Poisson-Inverse Gaussian distribution",
      "topics": [
        "dist_poisson_inverse_gaussian"
      ]
    },
    {
      "page": "dist_sample",
      "title": "Sampling distribution",
      "topics": [
        "dist_sample"
      ]
    },
    {
      "page": "dist_student_t",
      "title": "The (non-central) location-scale Student t Distribution",
      "topics": [
        "dist_student_t"
      ]
    },
    {
      "page": "dist_studentized_range",
      "title": "The Studentized Range distribution",
      "topics": [
        "dist_studentized_range"
      ]
    },
    {
      "page": "dist_transformed",
      "title": "Modify a distribution with a transformation",
      "topics": [
        "dist_transformed"
      ]
    },
    {
      "page": "dist_truncated",
      "title": "Truncate a distribution",
      "topics": [
        "dist_truncated"
      ]
    },
    {
      "page": "dist_uniform",
      "title": "The Uniform distribution",
      "topics": [
        "dist_uniform"
      ]
    },
    {
      "page": "dist_weibull",
      "title": "The Weibull distribution",
      "topics": [
        "dist_weibull"
      ]
    },
    {
      "page": "dist_wrap",
      "title": "Create a distribution from p/d/q/r style functions",
      "topics": [
        "dist_wrap"
      ]
    },
    {
      "page": "family.distribution",
      "title": "Extract the name of the distribution family",
      "topics": [
        "family.distribution"
      ]
    },
    {
      "page": "generate.distribution",
      "title": "Randomly sample values from a distribution",
      "topics": [
        "generate.distribution"
      ]
    },
    {
      "page": "has_symmetry",
      "title": "Check if a distribution is symmetric",
      "topics": [
        "has_symmetry"
      ]
    },
    {
      "page": "hdr",
      "title": "Compute highest density regions",
      "topics": [
        "hdr"
      ]
    },
    {
      "page": "hdr.distribution",
      "title": "Highest density regions of probability distributions",
      "topics": [
        "hdr.distribution"
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