Class: distribution.mixture.class

Class to describe the mixture of distributions

Super classes

mastiff::R6.class.class -> mastiff::distribution.abstract.class -> mastiff::distribution.continuous.class -> distribution.mixture.class

Active bindings

n_distributions

the number of distributions in the mixture

distributions

the distributions in the mixture

weights

the weights of the distributions in the mixture

interfaces

the list of available class interfaces

Methods

Public methods

• distribution.mixture.class$new()

• distribution.mixture.class$d()

• distribution.mixture.class$p()

• distribution.mixture.class$q()

• distribution.mixture.class$r()

• distribution.mixture.class$clone()

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Method new()

Create a new object of class distribution.mixture.class

Usage

distribution.mixture.class$new(distributions, weights)

Arguments

distributions

list of distributions in the mixture

weights

vector of weights of the distributions in the mixture

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Method d()

Density function for a random variable of the mixture

Usage

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

Arguments

x

vector of quantiles.

log

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

---

Method p()

Evaluates the distribution function of the mixture

Usage

distribution.mixture.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 quantile function of the mixture

Usage

distribution.mixture.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 samples of the mixture

Usage

distribution.mixture.class$r(n)

Arguments

n

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

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Method clone()

The objects of this class are cloneable with this method.

Usage

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

Arguments

deep

Whether to make a deep clone.