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USE OF MARKOV CHAIN MONTE CARLO METHODS IN

A BAYESIAN ANALYSIS OF THE BLOCK AND

BASU BIVARIATE EXPONENTIAL DISTRIBUTION

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JORGE A. ACHCAR^{1} AND ROSELI A. LEANDRO^{2}

^{1} *Department of Computer Sciences and Statistics, ICMSC, University of São Paulo,*

C. P. 668, CEP 13560-970, São Carlos, S. P., Brazil

^{2} *Department of Mathematics and Statistics, ESALQ, University of São Paulo,*

C. P. 11, 13418-900, Piracicaba, S. P., Brazil
(Received August 19, 1996; revised June 30, 1997)

**Abstract.**
Metropolis algorithms along with Gibbs
steps are proposed to perform a Bayesian analysis for the
Block and Basu (ACBVE) bivariate exponential
distribution. We also consider the use of Gibbs sampling to
develop Bayesian inference for accelerated life tests
assuming a power rule model and the ACBVE distribution.
The methodology developed in this paper is exemplified with
two examples.

*Key words and phrases*:
Bivariate exponential
distribution, Gibbs sampling, Metropolis algorithm,
accelerated life testing.

**Source**
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