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imprecise101  

Introduction to Imprecise Probabilities
View on CRAN: Click here


Download and install imprecise101 package within the R console
Install from CRAN:
install.packages("imprecise101")

Install from Github:
library("remotes")
install_github("cran/imprecise101")

Install by package version:
library("remotes")
install_version("imprecise101", "0.2.2.4")



Attach the package and use:
library("imprecise101")
Maintained by
Chel Hee Lee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-02-01
Latest Update: 2023-02-01
Description:
An imprecise inference presented in the study of Walley (1996) 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.
How to cite:
Chel Hee Lee (2023). imprecise101: Introduction to Imprecise Probabilities. R package version 0.2.2.4, https://cran.r-project.org/web/packages/imprecise101. Accessed 26 Aug. 2026.
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Complete documentation for imprecise101
Functions, R codes and Examples using the imprecise101 R package
Some associated functions: betabinom . betadif . ibm . idm . 
Some associated R codes: walley1996.R .  Full imprecise101 package functions and examples
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