Bayesian inference from count data using discrete uniform priors.

We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. We report a Bayesian derivation of the posterior probability distribution of the population size using a binomial likelihood and non-c...

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Autores principales:	Federico Comoglio, Letizia Fracchia, Maurizio Rinaldi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a5f1839fbee145c7aef10beb53db7c63
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spelling	oai:doaj.org-article:a5f1839fbee145c7aef10beb53db7c632021-11-18T08:52:08ZBayesian inference from count data using discrete uniform priors.1932-620310.1371/journal.pone.0074388https://doaj.org/article/a5f1839fbee145c7aef10beb53db7c632013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24116003/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. We report 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. Our derivation yields a computationally feasible formula that can prove useful in a variety of statistical problems involving absolute quantification under uncertainty. We implemented our algorithm in the R package dupiR and compared it with a previously proposed Bayesian method based on a Gamma prior. As a showcase, we demonstrate that our inference framework can be used to estimate bacterial survival curves from measurements characterized by extremely low or zero counts and rather high sampling fractions. All in all, we provide a versatile, general purpose algorithm to infer population sizes from count data, which can find application in a broad spectrum of biological and physical problems.Federico ComoglioLetizia FracchiaMaurizio RinaldiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 10, p e74388 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Federico Comoglio Letizia Fracchia Maurizio Rinaldi Bayesian inference from count data using discrete uniform priors.
description	We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. We report 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. Our derivation yields a computationally feasible formula that can prove useful in a variety of statistical problems involving absolute quantification under uncertainty. We implemented our algorithm in the R package dupiR and compared it with a previously proposed Bayesian method based on a Gamma prior. As a showcase, we demonstrate that our inference framework can be used to estimate bacterial survival curves from measurements characterized by extremely low or zero counts and rather high sampling fractions. All in all, we provide a versatile, general purpose algorithm to infer population sizes from count data, which can find application in a broad spectrum of biological and physical problems.
format	article
author	Federico Comoglio Letizia Fracchia Maurizio Rinaldi
author_facet	Federico Comoglio Letizia Fracchia Maurizio Rinaldi
author_sort	Federico Comoglio
title	Bayesian inference from count data using discrete uniform priors.
title_short	Bayesian inference from count data using discrete uniform priors.
title_full	Bayesian inference from count data using discrete uniform priors.
title_fullStr	Bayesian inference from count data using discrete uniform priors.
title_full_unstemmed	Bayesian inference from count data using discrete uniform priors.
title_sort	bayesian inference from count data using discrete uniform priors.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/a5f1839fbee145c7aef10beb53db7c63
work_keys_str_mv	AT federicocomoglio bayesianinferencefromcountdatausingdiscreteuniformpriors AT letiziafracchia bayesianinferencefromcountdatausingdiscreteuniformpriors AT mauriziorinaldi bayesianinferencefromcountdatausingdiscreteuniformpriors
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Bayesian inference from count data using discrete uniform priors.

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