imPois: Imprecise Inferential Framework for Poisson Sampling Model

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.

AuthorChel Hee Lee [aut, cre, cph], Mikelis Bickis [aut, ths, cph]
Date of publication2015-11-28 14:53:51
MaintainerChel Hee Lee <chl948@mail.usask.ca>
LicenseGPL (>= 2)
Version0.0.7.5
http://r-forge.r-project.org/projects/ipeglim/

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