USE OF MARKOV CHAIN MONTE CARLO METHODS IN A BAYESIAN ANALYSIS OF THE BLOCK AND BASU BIVARIATE EXPONENTIAL DISTRIBUTION

USE OF MARKOV CHAIN MONTE CARLO METHODS IN
A BAYESIAN ANALYSIS OF THE BLOCK AND
BASU BIVARIATE EXPONENTIAL DISTRIBUTION

JORGE A. ACHCAR¹ AND ROSELI A. LEANDRO²

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.

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