Class: distribution.discrete.beta_binomial.class — distribution.discrete.beta

Derived class for an beta-binomially distributed random variable.

Super classes

R6.class.class -> distribution.abstract.class -> distribution.discrete.class -> distribution.discrete.beta_binomial.class

interfaces: The list of available class interfaces
mean: The mean of a binomial distribution with size $params$size and success probability $params$prob.
sd: The standard deviation of a binomial distribution with size $params$size and success probability $params$prob.
var: The variance of a binomial distribution with size $params$size and success probability $params$prob.

Create a new object of class distribution.discrete.class

distribution.discrete.beta_binomial.class$new(size, alpha, beta)

Density function for a beta-binomial random variable with size params$size and shape parameters params$alpha and params$beta.

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

Cumulative density function for a beta-binomial random variable with size params$size and shape parameters params$alpha and params$beta.

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

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).

Quantile function for a beta-binomial random variable with size params$size and shape parameters params$alpha and params$beta.

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

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).

Generates random deviates for a beta-binomial random variable with size params$size and shape parameters params$alpha and params$beta.

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

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

The objects of this class are cloneable with this method.

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