ConvexContamination: Generic Function for Generating Convex Contaminations

In distrEx: Extensions of Package 'distr'

Generic Function for Generating Convex Contaminations

Description

Generic function for generating convex contaminations. This is also known as gross error model. Given two distributions P (ideal distribution), R (contaminating distribution) and the size \varepsilon\in [0,1] the convex contaminated distribution

Q = (1-epsilon)P + epsilon R

is generated.

Usage

ConvexContamination(e1, e2, size)

Arguments

e1	object of class "Distribution": ideal distribution
e2	object of class "Distribution": contaminating distribution
size	size of contamination (amount of gross errors)

Value

Object of class "Distribution".

Methods

e1 = "UnivariateDistribution", e2 = "UnivariateDistribution", size = "numeric":

convex combination of two univariate distributions

e1 = "AbscontDistribution", e2 = "AbscontDistribution", size = "numeric":

convex combination of two absolutely continuous univariate distributions

e1 = "DiscreteDistribution", e2 = "DiscreteDistribution", size = "numeric":

convex combination of two discrete univariate distributions

e1 = "AcDcLcDistribution", e2 = "AcDcLcDistribution", size = "numeric":

convex combination of two univariate distributions which may be coerced to "UnivarLebDecDistribution".

Author(s)

Matthias Kohl [e-mail]

References

Huber, P.J. (1981) Robust Statistics. New York: Wiley.

See Also

ContaminationSize, Distribution-class

Examples

# Convex combination of two normal distributions
C1 <- ConvexContamination(e1 = Norm(), e2 = Norm(mean = 5), size = 0.1)
plot(C1)

distrEx documentation built on Nov. 16, 2022, 1:07 a.m.