distrEx: ConvexContamination – R documentation

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ConvexContamination

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 Matthias.Kohl@stamats.de

References

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

Examples

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

distrEx

Extensions of Package 'distr'

v2.8.0

LGPL-3

Authors

Matthias Kohl [cre, cph], Peter Ruckdeschel [aut, cph]

Initial release

2019-03-29