rbeta.post: Random generation for the joint posterior distribution of the...

In santosneto/samplesizeBS: Bayesian sample size in a decision-theoretic approach for the Birbaum-Saunders

Description

A function for generating values from the joint posterior distribution of the Birnbaum-Saunders/inverse-gamma model.

Usage

rbeta.post(N, x, a1, b1, a2, b2, burnin, thin, start, varcov, scale = 1)

Arguments

N	number of observations.
x	vector of observed values of the model.
a1	hyperparameter of the prior distribution for beta.
b1	hyperparameter of the prior distribution for beta.
a2	hyperparameter of the prior distribution for shape^2.
b2	hyperparameter of the prior distribution for shape^2.
burnin	a positive constant for the sampling method.
thin	a positive constant for the sampling method.
start	a positive constant for the sampling method.
varcov	a positive constant for the sampling method.
scale	a positive constant for the sampling method.

Value

A random sample of the joint posterior distribution of the model Birnbaum-Saunders/inverse-gamma model.

Author(s)

Eliardo G. Costa [e-mail] and Manoel Santos-Neto [e-mail]

References

Wang, M., Sun, X. and Park, C. (2016) Bayesian analysis of Birnbaum-Saunders distribution via the generalized ratio-of-uniforms methods. Comput. Stat. 31: 207–225.

santosneto/samplesizeBS documentation built on May 23, 2021, 6:34 a.m.