BETABINOMIAL: Factory for a BETABINOMIAL distribution object

In convdistr: Convolute Probabilistic Distributions

Factory for a BETABINOMIAL distribution object

Description

Returns an BETABINOMIAL distribution object that produce random numbers from a betabinomial distribution using the rbbinom function

Usage

new_BETABINOMIAL(p_size, p_shape1, p_shape2, p_dimnames = "rvar")

new_BETABINOMIAL_od(p_size, p_mu, p_od, p_dimnames = "rvar")

new_BETABINOMIAL_icc(p_size, p_mu, p_icc, p_dimnames = "rvar")

Arguments

p_size	a non-negative parameter for the number of trials
p_shape1	non-negative parameters of the Betabinomial distribution
p_shape2	non-negative parameters of the Betabinomial distribution
p_dimnames	A character that represents the name of the dimension
p_mu	mean proportion for the binomial part of the distribution
p_od	over dispersion parameter
p_icc	intra-class correlation parameter

Value

An object of class DISTRIBUTION, BETADISTRIBUION

Functions

• new_BETABINOMIAL_od(): parametrization based on dispersion

• new_BETABINOMIAL_icc(): parametrization based on intra-class correlation

Note

There are several parametrization for the betabinomial distribution. The one based on shape1 and shape2 are parameters alpha and beta of the beta part of the distribution, but it can be parametrized as mu, and od where mu is the expected mean proportion and od is a measure of the overdispersion.

p_mu = p_shape1/(p_shape1 + p_shape2)

p_od = p_shape1 + p_shape2

p_shape1 = p_mu*p_od

p_shape2 <- (1-p_mu)*p_od

Another parametrization is based on mu and the icc where mu is the mean proportion and icc is the intra-class correlation.

p_mu = p_shape1/(p_shape1 + p_shape2)

p_icc = 1/(p_shape1 + p_shape2 + 1)

p_shape1 = p_mu*(1-p_icc)/p_icc

p_shape2 = (1-p_mu)*(1-p_icc)/p_icc

Author(s)

John J. Aponte

Examples

myDistr <- new_BETABINOMIAL(10,1,1)
myDistr$rfunc(10)

convdistr documentation built on May 29, 2024, 11:49 a.m.