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dst

Using Dempster-Shafer Theory of Evidence, also called "Theory of Belief Functions". Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values. Two mass functions on a variable A can be combined using Dempster's rule of combination. Relations between two variables A and B can be characterized by a mass functions defined on their product space A x B. A mass function on a variable A can be extended to the frame A x B. Dempster's rule of combination can be applied to product space. Marginalization, namely reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks described by an hypergraph and take into account situations where information cannot be satisfactorily described by probability distributions. An algorithm, the peeling, is provided to compute belief functions in a hypergraph.

Installation

Install from CRAN: install.package("dst")

Examples

See vignettes.

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Install

install.packages('dst')

Monthly Downloads

344

Version

1.8.0

License

GPL (>= 2)

Maintainer

Last Published

September 3rd, 2024

Functions in dst (1.8.0)

dlfm

The Captain's Problem. dlfm: Relation between variables Departure delay (D), Loading delay (L), Forecast of the weather (F), Maintenance delay (M)
commonality

Compute qq from tt
dst-package

Manipulation and combination of belief functions
matrixToMarray

Transformation of the tt matrix of a relation
encode

Convert a value to its representation in another chosen base
extFrame

Extension of the frame of discernment of a variable
marrayToMatrix

Transformation of an array data to its matrix representation
elim

Reduction of a relation
mobiusInvHQQ

Mobius inversion of commonality function
dsrwon

Combination of two mass functions
mFromQQ

Construct a mass vector from qq function.
nameCols_prod

Naming the columns of the tt matrix of a product space
mrf

The Captain's Problem. mrf: Relation between variables No Maintenance (M = false) and Repairs at sea (R)
dsrwonLogsumexp

Combination of two mass functions with logsumexp
nameRows

Combining the column names of a matrix to construct names for the rows
mFromQQRecursive

Construct a mass vector from qq function and ttmatrix of focal elements recursively.
peeling

The peeling algorithm
productSpace

Product space representation of a relation
plautrans

Plausibility transformation of the singletons of a frame
extmin

Extension of a relation
tabresul

Prepare a table of results
ttmatrix

Construct a description matrix from a list of subsets names.
inters

Intersection of two tables of propositions
intersBySSName

Intersect two vectors of ssnames
fw

The Captain's Problem. fw: Relation between variables Forecast of the weather (F) and Weather at sea (W)
shape

Obtain dimensions of an array or length of a vector with a single command
reduction

Summary of a vector for any operator.
dotprod

Generalized inner product of two matrices
swr

The Captain's Problem. swr: Relation between variables Sailing delay (S), Weather at sea (W), and Repairs at sea (R)
nzdsr

Normalization of a basic chance assignment
mFromMarginal

Construct m vector of a bca from marginal probabilities
doubles

Remove duplicate rows in a two-dimensional table.
logsum

Adding small probabilities
nzdsrLogsumexp

Normalization of a basic chance assignment with logsumexp
nameCols

Naming the columns of the tt matrix
ttmatrixFromMarginal

Construct tt matrix of a bca from marginal probabilities
ttmatrixPartition

Create partition matrix
mrt

The Captain's Problem. mrt: Relation between variables Maintenance done (M = true) and Repairs at sea (R)
ttmatrixFromQQ

Construct a description matrix from qq function.
bcaPrintLarge

Print summary statistics of large mass functions
bcaNorm

Computer norm between two basic chance assignment objects
ads

The Captain's Problem. ads: Relation between variables Arrival (A), Departure delay (D) and Sailing delay (S)
bca

Basic chance assignment mass function
bcaPrint

Simple printing of the tt matrix and mass values of a basic chance assignment (bca)
bcaRel

Representation of a mass function in a product space
belplau

Calculation of the degrees of Belief and Plausibility of a basic chance assignment (bca).
addTobca

Add some elements of 0 mass to an existing basic chance assignment.
bcaTrunc

Truncation of a basic chance assignment mass function
DoSSnames

Construct subsets names from column names of a tt matrix
belplauLogsumexp

Calculation of the degrees of Belief and Plausibility of a basic chance assignment (bca) with logsumexp.
decode

Find the value in base 10 of a number coded in another base
belplauPlot

Plot belplau matrix
belplauHLogsumexp

Calculate belief, disbelief, unknown, plausibility, plausibility ratio with logsumexp
belplauEval

Evaluate A, B errors
belplauHQQ

Compute belief, disbelief, unknown, plausibility, plausibility ratio based on commonality function
belplauH

Calculate belief, disbelief, unknown, plausibility, plausibility ratio
captain_result

The Captain's Problem. swr: Result of the evaluation of the Hypergraph at node Arrival (A)