belplau: Calculation of the degrees of Belief and Plausibility

Description Usage Arguments Details Value Author(s) References Examples

View source: R/belplau.R

Description

Degrees of Belief Bel and Plausibility Pl of the focal elements of a mass function are computed. The ratio of the plausibility of a focal element against the plausibility of its contrary is also computed. Subsets with zero mass can be excluded from the calculations.

Usage

1

Arguments

x

A basic chance assignment mass function (see bca).

remove

= TRUE: Exclude subsets with zero mass.

Details

The degree of belief Bel is defined by:

bel(A) = Sum((m(B); B <= A))

for every subset B of A.
The degree of plausibility pl is defined by:

pl(A) = Sum[(m(B); B and A not empty]

for every subset B of the frame of discernment.
The plausibility ratio of a focal element A versus its contrary not A is defined by: Pl(A)/(1-Bel(A)).

Value

A matrix of M rows by 3 columns is returned, where M is the number of focal elements:

Author(s)

Claude Boivin, Stat.ASSQ

References

Examples

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x <- bca(f=matrix(c(0,1,1,1,1,0,1,1,1),nrow=3, 
byrow = TRUE), m=c(0.2,0.5, 0.3), 
cnames =c("a", "b", "c"), infovarnames = "x", varnb = 1)
belplau(x)
y <- bca(f=matrix(c(1,0,0,1,1,1),nrow=2, 
byrow = TRUE), m=c(0.6, 0.4),  
cnames = c("a", "b", "c"),  infovarnames = "y", varnb = 1)
belplau(nzdsr(dsrwon(x,y)))
print("compare all elementary events")
xy1 <- addTobca(nzdsr(dsrwon(x,y)), 
matrix(c(0,1,0,0,0,1), nrow=2, byrow = TRUE))
belplau(xy1) 

dst documentation built on Dec. 5, 2018, 9:04 a.m.