Title: Imprecise Inferential Framework for Poisson Sampling Models
Authors@R: c(person(given="Chel Hee", family="Lee", email="chl948@mail.usask.ca", role=c("aut", "cre", "cph")), person(given="Mikelis", family="Bickis", role=c("aut", "ths", "cph"), email="bickis@snoopy.usask.ca"))
Author: Chel Hee Lee [aut, cre, cph], Mikelis Bickis [aut, ths, cph]
Maintainer: Chel Hee Lee <chl948@mail.usask.ca>
Contact: Chel Hee Lee <gnustats@gmail.com>
Description: A collection of tools needed for conducting imprecise inferential framework is provided.   Poisson sampling model and zero-truncated Poisson sampling models are mainly studied as the part of larger project, Imprecise Probability Estimates for Generalized Linear Model.  Imprecise probability theory introduced by Peter Wally in 1991 is the basis of this inference.
Imports: geometry, grDevices, stats, utils
BugReports: Chel Hee Lee <chl948@mail.usask.ca>

Title: Imprecise Inferential Framework for Poisson Sampling Model
Description: A collection of tools for conducting an imprecise inference is provided.   Imprecise prior is used for this inference, and imprecise probability theory introduced by Peter Walley (1991) is its underlying theoretical foundation.   The package is developed based on the PhD thesis work of Lee (2014).  Poisson and zero-truncated Poisson sampling models are mainly studied with two types of prior distributions.
Imports: geometry, grDevices, graphics, stats, utils, rgl

Title: Imprecise Inference for Poisson Sampling Models
Authors@R: c(person(given="Chel Hee", family="Lee", email="chl948@mail.usask.ca", role=c("aut", "cre", "cph")), person(given="Mikelis", family="Bickis", role=c("ths", "cph")))
Author: Chel Hee Lee [aut, cre, cph], Mikelis Bickis [ths, cph]
Description: Tools performing an imprecise inference for estimating the parameter of Poisson sampling model.   Extended the original work done in the PhD thesis of Lee (2014).   The theory of imprecise probabilities introduced by Peter Walley in 1991 becomes the basis of this inferential framework.