distr6 (version 1.3.6)

VectorDistribution: Vectorise Distributions

Description

A wrapper for creating a vector of distributions.

Value

Returns an R6 object of class VectorDistribution.

Constructor

VectorDistribution$new(distlist = NULL, distribution = NULL, params = NULL, name = NULL, short_name = NULL, description = NULL, decorators = NULL)

Constructor Arguments

Argument	Type	Details
distlist	list	List of distributions.
distribution	character	Distribution to wrap.
params	a R object	Either list of parameters or matrix-type frame, see examples.
shared_params	a R object	Either list of shared parameters or matrix-type frame, see examples.
name	list	Optional new name for distribution.
short_name	list	Optional new short_name for distribution.
description	list	Optional new description for distribution.
decorators	list	Decorators to pass to wrapped distributions on construction.

Constructor Details

A vector distribution can either be constructed by a list of distributions passed to distlist or by passing the name of one or more distributions implemented in distr6 to distribution, as well as a list or table of parameters to params. The former case provides more flexibility in the ability to use wrapped distributions but the latter is vastly faster for distributions of class SDistribution or custom distributions. The shared_params parameter decreases memory usage and improves speed by storing any parameters shared between distributions only once (instead of repeated in a list).

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

A vector distribution is intented to vectorize distributions more efficiently than storing a list of distributions. To improve speed and reduce memory usage, distributions are only constructed when methods (e.g. d/p/q/r) are called. Whilst it is recommended to first extract distributions using [ before querying them for results, all common methods are available in VectorDistribution as they are wrapped in apply.

See Also

listWrappers and ProductDistribution

Examples

# NOT RUN {
# not run to save time
# }
# NOT RUN {
vecDist <- VectorDistribution$new(list(Binomial$new(prob = 0.5,
                           size = 10), Normal$new(mean = 15)))
vecDist$pdf(x1 = 2, x2 =3)
# Equivalently
vecDist[1]$pdf(2); vecDist[2]$pdf(3)
# Or to evaluate every distribution at the same point
vecDist$pdf(1)

# Same wrapping for statistical functions
vecDist$mean()
c(vecDist[1]$mean(), vecDist[2]$mean())
vecDist$entropy()
c(vecDist[1]$entropy(), vecDist[2]$entropy())

vecDist$cdf(1:5, 12:16)
vecDist$rand(10)

vecBin = VectorDistribution$new(distribution = "Binomial",
       params = list(list(prob = 0.1, size = 2),
                   list(prob = 0.6, size = 4),
                   list(prob = 0.2, size = 6)))
vecBin$pdf(x1=1,x2=2,x3=3)
vecBin$cdf(x1=1,x2=2,x3=3)
vecBin$rand(10)

#Equivalently
vecBin = VectorDistribution$new(distribution = "Binomial",
       params = data.table::data.table(prob = c(0.1,0.6,0.2), size = c(2,4,6)))
vecBin$pdf(x1=1,x2=2,x3=3)
vecBin$cdf(x1=1,x2=2,x3=3)
vecBin$rand(10)

# sharedparams is very useful for vectorized custom distributions
shared_params = list(name = "A Distribution", short_name = "Dist", type = Reals$new())
params = list(list(pdf = function(x) return(1)), list(pdf = function(x) return(2)))
vecdist = VectorDistribution$new(distribution = "Distribution", params = params,
                                   shared_params = shared_params)
vecdist$pdf(1)
# }
# NOT RUN {
# }