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dupiR  

Bayesian Inference from Count Data using Discrete Uniform Priors
View on CRAN: Click here


Download and install dupiR package within the R console
Install from CRAN:
install.packages("dupiR")

Install from Github:
library("remotes")
install_github("cran/dupiR")

Install by package version:
library("remotes")
install_version("dupiR", "1.2.1")



Attach the package and use:
library("dupiR")
Maintained by
Federico Comoglio
[Scholar Profile | Author Map]
First Published: 2013-06-20
Latest Update: 2024-03-21
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) .
How to cite:
Federico Comoglio (2013). dupiR: Bayesian Inference from Count Data using Discrete Uniform Priors. R package version 1.2.1, https://cran.r-project.org/web/packages/dupiR. Accessed 17 Feb. 2025.
Previous versions and publish date:
1.0 (2013-06-20 07:34), 1.1 (2013-08-06 21:39), 1.2 (2014-12-29 18:15)
Other packages that cited dupiR R package
View dupiR citation profile
Other R packages that dupiR depends, imports, suggests or enhances
Complete documentation for dupiR
Functions, R codes and Examples using the dupiR R package
Full dupiR package functions and examples
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