bibs (version 1.1.1)

referencebs: Computing the Bayesian estimators of the Birnbaum-Saunders (BS) distribution.

Description

Computing the Bayesian estimators of the BS distribution using reference prior proposed by Berger and Bernardo(1989). The joint distribution of the priors is \(\pi(\alpha,\beta)=1/(\alpha,\beta)\).

Usage

referencebs(x, CI = 0.95, M0 = 800, M = 1000)

Arguments

x

Vector of observations.

CI

Confidence level for constructing percentile and asymptotic confidence intervals. That is 0.95 by default.

M0

The number of sampler runs considered as burn-in.

M

The number of total sampler runs.

Value

A list including summary statistics of a Gibbs sampler for Bayesian inference including point estimation for the parameter, its standard error, and the corresponding \(100(1-\alpha)\%\) credible interval, goodness-of-fit measures, asymptotic \(100(1-\alpha)\%\) confidence interval (CI) and corresponding standard errors, and Fisher information matix.

References

J. O. Berger and J. M. Bernardo 1989. Estimating a product of means: Bayesian analysis with reference priors. Journal of the American Statistical Association, 84(405), 200-207.

Examples

# NOT RUN {
data(fatigue)
x <- fatigue
referencebs(x, CI = 0.95, M0 = 800, M = 1000)
# }