mass-class: Class `"mass"`

Description

Represents a mass function by a list of focal elements and corresponding mass. For more detail see mass.

Arguments

Objects from the Class

Objects can be created by credal.

Slots

focal:: a list of focal elements represented by statenames seperated by "/"
space:: the state space represented by a character vector

Methods

[: signature(x = "mass", i = "character", j = "missing"): extract focal elements
[[: signature(x = "mass", i = "character", j = "missing"): extract a single focal element
[<-: signature(x="mass", i="character", j="missing", value="ANY"): replace focal elements
[[<-: signature(x="mass", i="character", j="missing", value="ANY"): replace a single focal element
dComb: signature(x = "mass", y = "mass"): combine two mass functions by Dempster's combination
focal: signature(x = "mass"): access focal elements
focal<-: signature(x = "mass"): replace focal elements
lower: signature(x = "mass", set = "character"): calculate the lower bounds for some focal element
lower: signature(x = "mass", set = "missing"): calculate the lower bounds for singletons
mComb: signature(x = "mass", y = "mass", z = "function"): combine two mass functions by modified Dempster's combination using a prior distribution z
mComb: signature(x = "mass", y = "mass", z = "missing"): combine two mass functions by modified Dempster's combination using a uniform prior distribution z
pign: signature(x = "mass"): calculate the pignistic transformation for single states
relPl: signature(x = "mass"): calculate the relative plausibility for single states
space: signature(x = "mass"): access the state space (frame of discernment)
space<-: signature(x = "mass"): replace the state space (frame of discernment)
upper: signature(x = "mass", set = "character"): calculate the upper bound for some focal element
upper: signature(x = "mass", set = "character"): calculate the upper bounds for singletons
yComb: signature(x = "mass", y = "mass"): combine two mass functions using Yager's rule
disc: signature(x = "mass", y = "numeric"): discount mass function

References

Dempster, A. P. (1969), A generalization of Bayesian inference, Journal of the Royal Statistical Society, 30, 205-247

Shafer, G., (1976), A Mathematical Theory of Evidence Princeton University Press

Yager, R. (1987), On the Dempster-Shafer Framework and New Combination Rules, Information Sciences 41: 93-137.

Fixsen, D., Mahler, R. P. S. (1997), The modified Dempster-Shafer approach to classification, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 27, 96-104