dupiR-package: Bayesian inference using discrete uniform priors with R

In dupiR: Bayesian inference from count data using discrete uniform priors

Description

This package implements a Bayesian approach to infer population sizes from count data. The package takes a set of sample counts obtained by sampling fractions of a finite volume containing an homogeneously dispersed population of identical objects and returns the posterior probability distribution of the population size. The algorithm makes use of a binomial likelihood and non-conjugate, discrete uniform priors. dupiR can be applied to both sampling with or without replacement.

Details

Package:	dupiR
Type:	Package
Version:	1.2
Date:	2014-12-29
License:	GPL-2

Author(s)

Federico Comoglio (1) and Maurizio Rinaldi (2)

(1) Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich, Switzerland

(2) Dipartimento di Scienze del Farmaco, Universita' del Piemonte Orientale

Maintainer: Federico Comoglio

[e-mail]

References

Comoglio F, Fracchia L and Rinaldi M (2013) Bayesian inference from count data using discrete uniform priors. PLOS ONE, 8(10):e74388. doi:10.1371/journal.pone.0074388

dupiR documentation built on May 2, 2019, 3:43 a.m.