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  "Title": "Bayesian Inference from Count Data using Discrete Uniform Priors",
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  "Description": "We consider a set of sample counts obtained by sampling\narbitrary fractions of a finite volume containing an\nhomogeneously dispersed population of identical objects. This\npackage implements a Bayesian derivation of the posterior\nprobability distribution of the population size using a\nbinomial likelihood and non-conjugate, discrete uniform priors\nunder sampling with or without replacement. This can be used\nfor a variety of statistical problems involving absolute\nquantification under uncertainty. See Comoglio et al. (2013)\n<doi:10.1371/journal.pone.0074388>.",
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    "compute_posterior",
    "get_counts",
    "get_fractions",
    "get_posterior_param",
    "new_counts",
    "plot",
    "plot_posterior",
    "set_counts<-",
    "set_fractions<-",
    "summary"
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  "_help": [
    {
      "page": "dupiR-package",
      "title": "Bayesian inference from count data using discrete uniform priors",
      "topics": [
        "dupiR-package",
        "dupiR"
      ]
    },
    {
      "page": "compute_ecdf",
      "title": "Compute ECDF (empirical cumulative distribution function)",
      "topics": [
        "compute_ecdf"
      ]
    },
    {
      "page": "compute_normalization_constant",
      "title": "Compute normalization constant",
      "topics": [
        "compute_normalization_constant"
      ]
    },
    {
      "page": "compute_posterior",
      "title": "Compute the posterior probability distribution of the population size for an object of class 'Counts'",
      "topics": [
        "compute_posterior"
      ]
    },
    {
      "page": "compute_posterior_with_replacement",
      "title": "Compute posterior probability with replacement",
      "topics": [
        "compute_posterior_with_replacement"
      ]
    },
    {
      "page": "compute_sum",
      "title": "Compute sum of terms (function F, Comoglio et al.)",
      "topics": [
        "compute_sum"
      ]
    },
    {
      "page": "compute_term",
      "title": "Compute single term (function F, Comoglio et al.)",
      "topics": [
        "compute_term"
      ]
    },
    {
      "page": "Counts-class",
      "title": "An S4 class to store measurements (count data, sampling fractions), prior support and posterior parameters",
      "topics": [
        "compute_posterior,Counts-method",
        "Counts-class",
        "get_counts,Counts-method",
        "get_fractions,Counts-method",
        "get_posterior_param,Counts-method",
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    },
    {
      "page": "gamma_poisson_clough",
      "title": "Compute posterior probability using a Gamma-Poisson model (Clough et al.)",
      "topics": [
        "gamma_poisson_clough"
      ]
    },
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      "title": "Get 'counts' slot for an object of class 'Counts'",
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      ]
    },
    {
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      "title": "Get 'fractions' slot for an object of class 'Counts'",
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        "get_fractions"
      ]
    },
    {
      "page": "get_posterior_param",
      "title": "Compute posterior probability distribution parameters (e.g. credible intervals) for an object of class 'Counts'",
      "topics": [
        "get_posterior_param"
      ]
    },
    {
      "page": "initialize-Counts-method",
      "title": "Initialize 'Counts' class",
      "topics": [
        "initialize,Counts-method"
      ]
    },
    {
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      "title": "Constructor for 'Counts' class",
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        "new_counts"
      ]
    },
    {
      "page": "plot_posterior",
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        "plot_posterior"
      ]
    },
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        "plot,Counts-method"
      ]
    },
    {
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      "title": "Set 'counts' slot for an object of class 'Counts'",
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        "set_counts<-"
      ]
    },
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        "set_fractions<-"
      ]
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