distr6 (version 1.6.9)

HuberizedDistribution: Distribution Huberization Wrapper

Description

A wrapper for huberizing any probability distribution at given limits.

Super classes

distr6::Distribution -> distr6::DistributionWrapper -> HuberizedDistribution

Active bindings

properties

Returns distribution properties, including skewness type and symmetry.

Methods

Public methods

• HuberizedDistribution$new()

• HuberizedDistribution$clone()

• distr6::Distribution$cdf()

• distr6::Distribution$confidence()

• distr6::Distribution$correlation()

• distr6::Distribution$getParameterValue()

• distr6::Distribution$iqr()

• distr6::Distribution$liesInSupport()

• distr6::Distribution$liesInType()

• distr6::Distribution$median()

• distr6::Distribution$parameters()

• distr6::Distribution$pdf()

• distr6::Distribution$prec()

• distr6::Distribution$print()

• distr6::Distribution$quantile()

• distr6::Distribution$rand()

• distr6::Distribution$setParameterValue()

• distr6::Distribution$stdev()

• distr6::Distribution$strprint()

• distr6::Distribution$summary()

• distr6::Distribution$workingSupport()

• distr6::DistributionWrapper$wrappedModels()

Method new()

Creates a new instance of this R6 class.

Usage

HuberizedDistribution$new(distribution, lower = NULL, upper = NULL)

Arguments

distribution

([Distribution]) Distribution to wrap.

lower

(numeric(1)) Lower limit to huberize the distribution at. If NULL then the lower bound of the Distribution is used.

upper

(numeric(1)) Upper limit to huberize the distribution at. If NULL then the upper bound of the Distribution is used.

Examples

HuberizedDistribution$new(
  Binomial$new(prob = 0.5, size = 10),
  lower = 2, upper = 4
)

# alternate constructor huberize(Binomial$new(), lower = 2, upper = 4)

Method clone()

The objects of this class are cloneable with this method.

Usage

HuberizedDistribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Details

The pdf and cdf of the distribution are required for this wrapper, if unavailable decorate with FunctionImputation first.

Huberizes a distribution at lower and upper limits, using the formula $$f_H(x) = F(x), if x \le lower$$ $$f_H(x) = f(x), if lower < x < upper$$ $$f_H(x) = F(x), if x \ge upper$$ where f_H is the pdf of the truncated distribution H = Huberize(X, lower, upper) and \(f_X\)/\(F_X\) is the pdf/cdf of the original distribution.

See Also

Other wrappers: Convolution, DistributionWrapper, MixtureDistribution, ProductDistribution, TruncatedDistribution, VectorDistribution

Examples

# NOT RUN {
## ------------------------------------------------
## Method `HuberizedDistribution$new`
## ------------------------------------------------

HuberizedDistribution$new(
  Binomial$new(prob = 0.5, size = 10),
  lower = 2, upper = 4
)

# alternate constructor
huberize(Binomial$new(), lower = 2, upper = 4)
# }