Class: distribution.discrete.class

Base class for univariate discrete distributions

Super classes

mastiff::R6.class.class -> mastiff::distribution.abstract.class -> distribution.discrete.class

Active bindings

interfaces

The list of available class interfaces.

support

The support of the continuous distribution, i.e. the subset of values for which the density is positive,

Methods

Public methods

• distribution.discrete.class$new()

• distribution.discrete.class$p()

• distribution.discrete.class$q()

• distribution.discrete.class$clone()

Inherited methods

• mastiff::distribution.abstract.class$d()
• mastiff::distribution.abstract.class$r()

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Method new()

Create a new object of class distribution.discrete.class

Usage

distribution.discrete.class$new(support = c(0, Inf))

Arguments

support

The support of the distribution, i.e. the subset of integers for which the density is positive.

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Method p()

Evaluates the distribution function of a discrete random variable with finite integer support given density function $d()

Usage

distribution.discrete.class$p(q, lower.tail = TRUE, log.p = FALSE)

Arguments

q

vector of quantiles.

lower.tail

logical; if TRUE (default), probabilities are \(P[ X \leq x ]\), otherwise, \(P[X>x]\).

log.p

logical; if TRUE, probabilities p are given as log(p).

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Method q()

Evaluates the distribution function of a discrete random variable with finite integer support given distribution function $p()

Usage

distribution.discrete.class$q(p, lower.tail = TRUE, log.p = FALSE)

Arguments

p

vector of probabilities.

lower.tail

logical; if TRUE (default), probabilities are \(P[ X \leq x ]\), otherwise, \(P[X>x]\).

log.p

logical; if TRUE, probabilities p are given as log(p).

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Method clone()

The objects of this class are cloneable with this method.

Usage

distribution.discrete.class$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.