Distribution: Generalised Distribution Object

Description

A generalised distribution object for defining custom probability distributions as well as serving as the parent class to specific, familiar distributions.

Value

Returns R6 object of class Distribution.

Constructor

Distribution$new(name = NULL, short_name = NULL, type = NULL, support = NULL, symmetric = FALSE, pdf = NULL, cdf = NULL, quantile = NULL, rand = NULL, parameters = NULL, decorators = NULL, valueSupport = NULL, variateForm = NULL, description = NULL, suppressMoments = TRUE)

Constructor Arguments

Argument	Type	Details
`name`	character	Full name of distribution.
`short_name`	character	Short name to identify distribution.
`type`	set6::Set	Scientific type.
`support`	set6::Set	Distribution support. See Details.
`symmetric`	logical	Is distribution symmetric?
`pdf`	function	See Details.
`cdf`	function	See Details.
`quantile`	function	See Details.
`rand`	function	See Details.
`parameters`	ParameterSet	See Details.
`decorators`	list	R6 decorators to add in construction.
`valueSupport`	character	continuous, discrete, mixture. See Details.
`variateForm`	character	univariate, multivariate, matrixvariate. See Details.
`description`	character	Short description of distribution.
`suppressMoments`	character	See Details.

Constructor Details

The most basic Distribution object consists of a name and one of pdf/cdf.

If supplied, type and support should be given as a set6::Set object. If neither are supplied then the set of Reals is taken to be the type and the dimension is the number of formal arguments in the pdf/cdf. If only type is supplied then this is taken to also be the support.

By default, missing pdf, cdf, quantile and rand are not automatically imputed. Use the FunctionImputation decorator to generate these.

See ParameterSet for more details on construction of a ParameterSet.

decorators is an optional list of decorators (R6 environments not strings) to decorate the Distribution in construction. Decorators can also be added after construction. See decorate for more details.

valueSupport should be one of continuous/discrete/mixture if supplied. variateForm should be one of univariate/multivariate/matrixvariate if supplied. If not given these are automatically filled from type and support.

suppressMoments can be used to prevent the skewness and kurtosis type being automatically calculated in construction. This has the benefit of drastically decreasing computational time but at the cost of losing these in the distribution properties.

Public Variables

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

Public Methods

Accessor Methods	Link
`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`
`correlation()`	`correlation`



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`

Active Bindings

Active Binding	Link
`isPdf`	`isPdf`
`isCdf`	`isCdf`
`isQuantile`	`isQuantile`
`isRand`	`isRand`