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Class: distribution.discrete.negative_binomial.class

Source: R/distribution_discrete.R
distribution.discrete.negative_binomial.class.Rd

Derived class for an negative binomially-distributed random variable.

Super classes

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

Active bindings

interfaces

The list of available class interfaces

params

Named list of distribution parameters

mean

The mean of a negative_binomial distribution with mean $params$lambda.

sd

The standard deviation of a negative_binomial distribution with mean $params$lambda.

var

The variance of a negative_binomial distribution with mean $params$lambda.

Methods

Public methods

Method new()

Create a new object of class distribution.discrete.negative_binomial.class

Usage

distribution.discrete.negative_binomial.class$new(size, prob, mu)

Arguments

size

target for number of successful trials, or dispersion parameter (the shape parameter of the gamma mixing distribution). Must be strictly positive, need not be integer.

prob

probability of success in each trial. 0 < prob <= 1.

mu

alternative parametrization via mean: see stats::dnbinom

Method d()

Density function for a negative_binomial random variable with size params$size and success probability params$prob.

Usage

distribution.discrete.negative_binomial.class$d(x, log = FALSE)

Arguments

x

vector of quantiles.

log

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

Method p()

Cumulative density function for a negative_binomial random variable with size params$size and success probability params$prob.

Usage

distribution.discrete.negative_binomial.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).

Method q()

Quantile function for a negative_binomial random variable with size params$size and success probability params$prob.

Usage

distribution.discrete.negative_binomial.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).

Method r()

Generates random deviates for a negative_binomial random variable with size params$size and success probability params$prob.

Usage

distribution.discrete.negative_binomial.class$r(n)

Arguments

n

number of observations. If length( n ) > 1, the length is taken to be the number required.

Method clone()

The objects of this class are cloneable with this method.

Usage

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

Arguments

deep

Whether to make a deep clone.