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Factory for a BETABINOMIAL distribution object

Source: R/distributions.R
BETABINOMIAL.Rd

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

John J. Aponte

Examples

myDistr <- new_BETABINOMIAL(10,1,1)
myDistr$rfunc(10)
#>    rvar
#> 1     6
#> 2     0
#> 3     7
#> 4     6
#> 5     2
#> 6     2
#> 7     8
#> 8     0
#> 9     8
#> 10   10