dupiR-package

dupiR

This package allows to infer population sizes using a binomial likelihood 
and least informative discrete uniform priors.

package

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

Bayesian Inference from Count Data using Discrete Uniform Priors

Maurizio Rinaldi

dupiR-package function

Federico Comoglio <a href="/link/federico.comoglio%40gmail.com?package=dupiR&version=1.2.1" data-mini-rdoc="dupiR::federico.comoglio@gmail.com">federico.comoglio@gmail.com</a>
Maurizio Rinaldi

Author

Bayesian inference from count data using discrete uniform priors — dupiR-package

Federico Comoglio <a href='mailto:federico.comoglio@gmail.com'>federico.comoglio@gmail.com</a>
Maurizio Rinaldi

dupiR-package: Bayesian inference from count data using discrete uniform priors

Description

Arguments

Author

References