compute_posterior_with_replacement

Compute posterior probability with replacement

We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. This package implements a Bayesian derivation of the posterior probability distribution of the population size using a binomial likelihood and non-conjugate, discrete uniform priors under sampling with or without replacement. This can be used for a variety of statistical problems involving absolute quantification under uncertainty. See Comoglio et al. (2013) <doi:10.1371/journal.pone.0074388>.

Federico Comoglio

dupiR

Bayesian Inference from Count Data using Discrete Uniform Priors

Maurizio Rinaldi

compute_posterior_with_replacement function

<dl><dt>n</dt>
<dd>integer for which to compute the posterior</dd>
<dt>counts</dt>
<dd>integer vector of counts</dd>
<dt>f_product</dt>
<dd>product of (1-<code>fractions</code>)</dd>
<dt>denominator</dt>
<dd>normalization constant returned by <code>compute_normalization_constant</code></dd></dl>

Arguments

Compute posterior probability with replacement — compute_posterior_with_replacement

<dl>

<dt>n</dt>
<dd>integer for which to compute the posterior</dd>


<dt>counts</dt>
<dd>integer vector of counts</dd>


<dt>f_product</dt>
<dd>product of (1-<code>fractions</code>)</dd>


<dt>denominator</dt>
<dd>normalization constant returned by <code>compute_normalization_constant</code></dd>

</dl>

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compute_posterior_with_replacement: Compute posterior probability with replacement

Description

Usage

Value

Arguments

See Also