Package: dupiR 1.2.1

dupiR: 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. 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>.

Authors:Federico Comoglio [aut, cre], Maurizio Rinaldi [aut]

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NEWS

# Install 'dupiR' in R:
install.packages('dupiR', repos = c('https://federicocomoglio.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/federicocomoglio/dupir/issues

On CRAN:

bayesian-inference

10 exports 1 stars 1.18 score 1 dependencies 1 mentions 7 scripts 194 downloads

Last updated 6 months agofrom:ddb65a941a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 19 2024
R-4.5-winOKAug 19 2024
R-4.5-linuxOKAug 19 2024
R-4.4-winOKAug 19 2024
R-4.4-macOKAug 19 2024
R-4.3-winOKAug 19 2024
R-4.3-macOKAug 19 2024

Exports:compute_posteriorget_countsget_fractionsget_posterior_paramnew_countsplotplot_posteriorset_counts<-set_fractions<-summary

Dependencies:plotrix

Readme and manuals

Help Manual

Help pageTopics
Bayesian inference from count data using discrete uniform priorsdupiR-package dupiR
Compute ECDF (empirical cumulative distribution function)compute_ecdf
Compute normalization constantcompute_normalization_constant
Compute the posterior probability distribution of the population size for an object of class 'Counts'compute_posterior
Compute posterior probability with replacementcompute_posterior_with_replacement
Compute sum of terms (function F, Comoglio et al.)compute_sum
Compute single term (function F, Comoglio et al.)compute_term
An S4 class to store measurements (count data, sampling fractions), prior support and posterior parameterscompute_posterior,Counts-method Counts-class get_counts,Counts-method get_fractions,Counts-method get_posterior_param,Counts-method plot_posterior,Counts-method set_counts<-,Counts-method set_fractions<-,Counts-method
Compute posterior probability using a Gamma-Poisson model (Clough et al.)gamma_poisson_clough
Get 'counts' slot for an object of class 'Counts'get_counts
Get 'fractions' slot for an object of class 'Counts'get_fractions
Compute posterior probability distribution parameters (e.g. credible intervals) for an object of class 'Counts'get_posterior_param
Initialize 'Counts' classinitialize,Counts-method
Constructor for 'Counts' classnew_counts
Plot posterior probability distribution and display posterior parameters for an object of class 'Counts'plot_posterior
Plot method for 'Counts' classplot,Counts-method
Set 'counts' slot for an object of class 'Counts'set_counts<-
Set 'fractions' slot for an object of class 'Counts'set_fractions<-
Print method for 'Counts' classshow,Counts-method
Summary method for 'Counts' classsummary,Counts-method