dst

Using the Theory of Belief Functions

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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Package
dst
Type
Package
Title
Using the Theory of Belief Functions
Encoding
UTF-8
Version
1.3.0
Date
2018-11-30
Author
Claude Boivin, Stat.ASSQ
Maintainer
Claude Boivin
Description
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.
License
GPL (>= 2)
BugReports
https://github.com/RAPLER/dst-1/issues
Collate
'addTobca.R' 'bca.R' 'bcaRel.R' 'belplau.R' 'decode.R' 'dotprod.R' 'doubles.R' 'dsrwon.R' 'dst.R' 'elim.R' 'encode.R' 'extmin.R' 'inters.R' 'marrayToMatrix.R' 'matrixToMarray.R' 'nameRows.R' 'nzdsr.R' 'plautrans.R' 'productSpace.R' 'reduction.R' 'shape.R' 'tabresul.R'
RoxygenNote
6.1.1
Suggests
testthat, knitr, rmarkdown, igraph
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2018-12-05 02:19:51 UTC; chrono03
Repository
CRAN
Date/Publication
2018-12-05 06:10:03 UTC

install.packages('dst')

1.3.0

4 days ago

Claude Boivin

GPL (>= 2)

Suggests

testthat, knitr, rmarkdown, igraph

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