ConvexContamination

0th

Percentile

Generic Function for Generating Convex Contaminations

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 $$Q = (1-\varepsilon)P + \varepsilon R$$ is generated.

Keywords
methods, distribution
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".

concept

  • convex contamination
  • gross error
  • univariate distribution
  • absolutely continuous distribution
  • discrete distribution
  • S4 distribution class

References

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

See Also

ContaminationSize, Distribution-class

Aliases
  • ConvexContamination
  • ConvexContamination-methods
  • ConvexContamination,UnivariateDistribution,UnivariateDistribution,numeric-method
  • ConvexContamination,AbscontDistribution,AbscontDistribution,numeric-method
  • ConvexContamination,AbscontDistribution,UnivariateDistribution,numeric-method
  • ConvexContamination,DiscreteDistribution,DiscreteDistribution,numeric-method
Examples
# Convex combination of two normal distributions
C1 <- ConvexContamination(e1 = Norm(), e2 = Norm(mean = 5), size = 0.1)
plot(C1)
Documentation reproduced from package distrEx, version 1.9, License: GPL (version 2 or later)

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