Some basic functions to implement belief functions including: transformation between belief functions using the method introduced by Philippe Smets (arXiv:1304.1122 [cs.AI]), evidence combination, evidence discounting, decision-making, and constructing masses. Currently, thirteen combination rules and five decision rules are supported. It can also be used to generate different types of random masses when working on belief combination and conflict management.
|Author||Kuang Zhou <firstname.lastname@example.org>; Arnaud Martin <email@example.com>|
|Date of publication||2015-07-16 14:24:30|
|Maintainer||Kuang Zhou <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
|Installation||Install the latest version of this package by entering the following in R:
|ConflictTable: Computing the conflict table|
|decisionDST: Decision Rules|
|discounting: Discounting masses|
|DST: Combination rules|
|FMTfunctions: Fast Mobius Transform|
|LCPrincple: Least-Committed Principle for creating bbas|
|PCR6: PCR6 rule|
|RandomMass: Generating masses|
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