imprecise101: Introduction to Imprecise Probabilities

An imprecise inference presented in the study of Walley (1996) <doi:10.1111/j.2517-6161.1996.tb02065.x> is one of the statistical reasoning methods when prior information is unavailable. Functions and utils needed for illustrating this inferential paradigm are implemented for classroom teaching and further comprehensive research. Two imprecise models are demonstrated using multinomial data and 2x2 contingency table data. The concepts of prior ignorance and imprecision are discussed in lower and upper probabilities. Representation invariance principle, hypothesis testing, decision-making, and further generalization are also illustrated.

Version: 0.2.2.4
Imports: stats, tolerance, graphics, pscl
Suggests: covr, knitr, rmarkdown
Published: 2023-02-01
Author: Chel Hee Lee ORCID iD [aut, cre], Mikelis Bickis [ctb], Angela McCourt [ctb]
Maintainer: Chel Hee Lee <chelhee.lee at ucalgary.ca>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: imprecise101 results

Documentation:

Reference manual: imprecise101.pdf
Vignettes: example

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Package source: imprecise101_0.2.2.4.tar.gz
Windows binaries: r-devel: imprecise101_0.2.2.4.zip, r-release: imprecise101_0.2.2.4.zip, r-oldrel: imprecise101_0.2.2.4.zip
macOS binaries: r-release (arm64): imprecise101_0.2.2.4.tgz, r-oldrel (arm64): imprecise101_0.2.2.4.tgz, r-release (x86_64): imprecise101_0.2.2.4.tgz

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