dupiR: Bayesian inference from count data using discrete uniform priors

Inference of population sizes using a binomial likelihood and least informative discrete uniform priors.

Author
Federico Comoglio and Maurizio Rinaldi
Date of publication
2014-12-29 18:15:37
Maintainer
Federico Comoglio <federico.comoglio@bsse.ethz.ch>
License
GPL-2
Version
1.2

View on CRAN

Man pages

accessors
Accessors for the 'counts' and 'fractions' slots of a Counts...
computePosterior
Compute the posterior probability distribution of the...
Counts-class
Class "Counts" - a container for measurements and dupiR...
dupiR-package
Bayesian inference using discrete uniform priors with R
getPosteriorParam
Compute posterior probability distribution parameters
newCounts
Construct an object of class Counts
plotPosterior
Plot posterior probability distributions

Files in this package

dupiR
dupiR/inst
dupiR/inst/CITATION
dupiR/NAMESPACE
dupiR/NEWS
dupiR/R
dupiR/R/privatefun.R
dupiR/R/methods.R
dupiR/R/class.R
dupiR/MD5
dupiR/DESCRIPTION
dupiR/man
dupiR/man/plotPosterior.Rd
dupiR/man/getPosteriorParam.Rd
dupiR/man/Counts-class.Rd
dupiR/man/dupiR-package.Rd
dupiR/man/newCounts.Rd
dupiR/man/computePosterior.Rd
dupiR/man/accessors.Rd