TruncatedDistribution: Distribution Truncation Wrapper

Description

A wrapper for truncating any probability distribution at given limits.

Value

Returns an R6 object of class TruncatedDistribution.

Constructor

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

Constructor Arguments

Argument	Type	Details
`distribution`	distribution	Distribution to truncate.
`lower`	numeric	Lower limit for truncation.

Public Variables

Variable	Return
`name`	Name of distribution.
`short_name`	Id of distribution.
`description`	Brief description of distribution.

Public Methods

Accessor Methods	Link
`wrappedModels(model = NULL)`	`wrappedModels`
`decorators()`	`decorators`
`traits()`	`traits`
`valueSupport()`	`valueSupport`
`variateForm()`	`variateForm`
`type()`	`type`
`properties()`	`properties`
`support()`	`support`
`symmetry()`	`symmetry`
`sup()`	`sup`
`inf()`	`inf`
`dmax()`	`dmax`
`dmin()`	`dmin`
`skewnessType()`	`skewnessType`
`kurtosisType()`	`kurtosisType`



d/p/q/r Methods	Link
`pdf(x1, ..., log = FALSE, simplify = TRUE)`	`pdf`
`cdf(x1, ..., lower.tail = TRUE, log.p = FALSE, simplify = TRUE)`	`cdf`
`quantile(p, ..., lower.tail = TRUE, log.p = FALSE, simplify = TRUE)`	`quantile.Distribution`
`rand(n, simplify = TRUE)`	`rand`



Statistical Methods	Link
`prec()`	`prec`
`stdev()`	`stdev`
`median()`	`median.Distribution`
`iqr()`	`iqr`
`cor()`	`cor`



Parameter Methods	Link
`parameters(id)`	`parameters`
`getParameterValue(id, error = "warn")`	`getParameterValue`
`setParameterValue(..., lst = NULL, error = "warn")`	`setParameterValue`



Validation Methods	Link
`liesInSupport(x, all = TRUE, bound = FALSE)`	`liesInSupport`
`liesInType(x, all = TRUE, bound = FALSE)`	`liesInType`



Representation Methods	Link
`strprint(n = 2)`	`strprint`
`print(n = 2)`	`print`
`summary(full = T)`	`summary.Distribution`

Details

Truncates a distribution at lower and upper limits, 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.

If lower or upper are NULL they are taken to be self$inf() and self$sup() respectively. The support of the new distribution is the interval of points between lower and upper.

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

Examples

Run this code

# NOT RUN {
truncBin <- TruncatedDistribution$new(
            Binomial$new(prob = 0.5, size = 10),
            lower = 2, upper = 4)
truncBin$getParameterValue("prob")

# }

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