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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>.
| Version: | 1.2.1 |
| Depends: | R (≥ 2.15.1), methods |
| Imports: | graphics, plotrix, stats, utils |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2024-03-21 |
| DOI: | 10.32614/CRAN.package.dupiR |
| Author: | Federico Comoglio [aut, cre], Maurizio Rinaldi [aut] |
| Maintainer: | Federico Comoglio <federico.comoglio at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | dupiR citation info |
| Materials: | README NEWS |
| CRAN checks: | dupiR results |
| Reference manual: | dupiR.pdf |
| Package source: | dupiR_1.2.1.tar.gz |
| Windows binaries: | r-devel: dupiR_1.2.1.zip, r-release: dupiR_1.2.1.zip, r-oldrel: dupiR_1.2.1.zip |
| macOS binaries: | r-release (arm64): dupiR_1.2.1.tgz, r-oldrel (arm64): dupiR_1.2.1.tgz, r-release (x86_64): dupiR_1.2.1.tgz, r-oldrel (x86_64): dupiR_1.2.1.tgz |
| Old sources: | dupiR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.