new_counts

Constructor for <code>Counts</code> class

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

new_counts function

<dl><dt>counts</dt>
<dd>integer vector of counts</dd>
<dt>fractions</dt>
<dd>numeric vector of sampling fractions</dd></dl>

Arguments

Constructor for Counts class — new_counts

<dl>

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


<dt>fractions</dt>
<dd>numeric vector of sampling fractions</dd>

</dl>

new_counts: Constructor for `Counts` class

Description

Usage

Value

Arguments