ArrayDistribution-deprecated: Product Array Distribution

Description

A special case product distribution where each independent distribution is the same Distribution class but not necessarily with the same parameters.

Value

Returns an R6 object of class ArrayDistribution.

Constructor

ArrayDistribution$new(distribution, paramList, name = NULL, short_name = NULL, description = NULL)

Constructor Arguments

Argument	Type	Details
`distribution`	distribution	Distribution to wrap.
`paramList`	list	List of parameters, see example.
`name`	list	Optional new name for distribution.
`short_name`	list	Optional new short_name for distribution.
`description`	list	Optional new description for distribution.

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

Exploits the following relationships of independent distributions $f_{A} (X 1 = x 1, . . ., X N = x N) = f_{X 1} (x 1) * . . . * f_{X N} (x n)$ $F_{A} (X 1 = x 1, . . ., X N = x N) = F_{X 1} (x 1) * . . . * F_{X N} (x n)$ where $f_{A}$ / $F_{A}$ is the pdf/cdf of the array distribution $A$ and $X 1, . . ., X N$ are independent distributions.

Examples

Run this code

# NOT RUN {
a = ArrayDistribution$new(Binomial,
              list(list(prob = 0.1, size = 2),
                   list(prob = 0.6, size = 4),
                   list(prob = 0.2, size = 6)))
a$pdf(x1=1,x2=2,x3=3)
a$cdf(x1=1,x2=2,x3=3)
a$rand(10)

# }

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