Package: dupiR
Type: Package
Title: Bayesian Inference from Count Data using Discrete Uniform Priors
Version: 1.2.1
Date: 2024-03-17
Depends: R (>= 2.15.1), methods
Authors@R: 
    c(person(given = "Federico",
           family = "Comoglio",
           role = c("aut", "cre"),
           email = "federico.comoglio@gmail.com"),
    person(given = "Maurizio",
           family = "Rinaldi",
           role = c("aut"),
           email = "maurizio.rinaldi@uniupo.it")
    )
Author: Federico Comoglio [aut, cre],
  Maurizio Rinaldi [aut]
Maintainer: Federico Comoglio <federico.comoglio@gmail.com>
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. 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>.
License: GPL-2
LazyLoad: yes
RoxygenNote: 7.3.1
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: graphics, plotrix, stats, utils
NeedsCompilation: no
Packaged: 2024-03-20 08:27:37 UTC; federicocomoglio
Repository: CRAN
Date/Publication: 2024-03-21 16:20:05 UTC
Built: R 4.3.3; ; 2025-01-24 06:53:54 UTC; unix
