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Using the Theory of Belief Functions

Installation

About

Using the Theory of Belief Functions for evidence calculus. Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values and combined. A mass function can be extended to a larger frame. Marginalization, i.e. reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks and take into account situations where information cannot be satisfactorily described by probability distributions.

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Key Metrics

Version 1.6.0
R ≥ 3.5.0
Published 2024-04-18 6 days ago
Needs compilation? yes
License GPL-2
License GPL-3
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Maintainer

Maintainer

Claude Boivin

webapp.cb@gmail.com

Authors

Claude Boivin Peiyuan Zhu

Material

README
NEWS
Reference manual
Package source

Vignettes

Bayes_Rule
Captain_Example
Crime_Scene
Introduction to Belief Functions
The Monty Hall Game
The original peter, John and Mary example
Peeling algorithm on Zadeh's Example

macOS

r-prerel

arm64

r-release

arm64

r-oldrel

arm64

r-prerel

x86_64

r-release

x86_64

Windows

r-prerel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

dst archive

Depends

R ≥ 3.5.0

Imports

dplyr
ggplot2
tidyr
Matrix
methods
parallel
rlang
utils

Suggests

igraph
knitr
rmarkdown
tidyverse
testthat