Distribution Truncation Wrapper

A wrapper for truncating any probability distribution at given limits.

Details

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

Truncates a distribution at lower and upper limits on a left-open interval, using the formulae $$f_T(x) = f_X(x) / (F_X(upper) - F_X(lower))$$ $$F_T(x) = (F_X(x) - F_X(lower)) / (F_X(upper) - F_X(lower))$$ where \(f_T\)/\(F_T\) is the pdf/cdf of the truncated distribution T = Truncate(X, lower, upper) and \(f_X\), \(F_X\) is the pdf/cdf of the original distribution. T is supported on (].

See also

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

Super classes

distr6::Distribution -> distr6::DistributionWrapper -> TruncatedDistribution

Active bindings

properties

Returns distribution properties, including skewness type and symmetry.

Methods

Public methods

• TruncatedDistribution$new()

• TruncatedDistribution$clone()

Inherited methods

• 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

TruncatedDistribution$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

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

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

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TruncatedDistribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## ------------------------------------------------
## Method `TruncatedDistribution$new`
## ------------------------------------------------

TruncatedDistribution$new(
  Binomial$new(prob = 0.5, size = 10),
  lower = 2, upper = 4
)
#> TruncBinom(Binom__prob = 0.5, Binom__size = 10, trunc__lower = 2, trunc__upper = 4) 

# alternate constructor
truncate(Binomial$new(), lower = 2, upper = 4)
#> TruncBinom(Binom__prob = 0.5, Binom__size = 10, trunc__lower = 2, trunc__upper = 4)