Browse > Article

A BAYESIAN ANALYSIS FOR PRODUCT OF POWERS OF POISSON RATES  

KIM HEA-JUNG (Department of Statistics, Dongguk University)
Publication Information
Journal of the Korean Statistical Society / v.34, no.2, 2005 , pp. 85-98 More about this Journal
Abstract
A Bayesian analysis for the product of different powers of k independent Poisson rates, written ${\theta}$, is developed. This is done by considering a prior for ${\theta}$ that satisfies the differential equation due to Tibshirani and induces a proper posterior distribution. The Gibbs sampling procedure utilizing the rejection method is suggested for the posterior inference of ${\theta}$. The procedure is straightforward to specify distributionally and to implement computationally, with output readily adapted for required inference summaries. A salient feature of the procedure is that it provides a unified method for inferencing ${\theta}$ with any type of powers, and hence it solves all the existing problems (in inferencing ${\theta}$) simultaneously in a completely satisfactory way, at least within the Bayesian framework. In two examples, practical applications of the procedure is described.
Keywords
Bayesian analysis; Product of powers of Poisson rates; Tibshirani's differential equation; the Gibbs sampling; the rejection method;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Datta, G. S. and Ghosh, M. (1996). 'On the invariance of noninformative priors,' The Annals of Staisitcs, 24, 141-159   DOI   ScienceOn
2 Environmental Protection Agency (1986). 'Bacteriological ambient water quality criteria for marine and fresh recreational waters,' Ambient Water Quality Criteria for Bacteria
3 Martz, H. F. and Wailer, R. A. (1982). Bayesian Reliability Analysis, John Wiley & Son, New York
4 Stein, C. (1985). 'On the coverage probability of confidence sets based on a prior distribution,' In Sequential Methods in Statistics, Banach center publications,16, Warsaw: PWN-Polish scientific publishers
5 Harris, B. (1971). 'Hypothesis testing and confidence intervals for products and quotients of Poisson parameters with applications to reliability,' Journal of the American Statistical Society, 66, 609-613   DOI   ScienceOn
6 Mukerjee, R. and Ghosh, M. (1997). 'Second order probability matching priors,' Biometrika, 84, 970-975   DOI   ScienceOn
7 Tibshirani, R. (1989) 'Noninformative priors for one parameter of many', Biometrika, 76, 604-608   DOI   ScienceOn
8 Chen, M. H., Shao, Q. M., and Ibrahim, J. G. (2000). Monte Carlo Methods in Bayesian Computation, New York: Springer
9 Gelfand, A. E. and Smith, A. F. M. (1990). 'Sampling based approaches to calculating marginal densities,' Journal of the American Statistical Association, 85, 398-409   DOI
10 Harris, B. and Soms, A. P. (1973). 'The reliability systems of independent parallel components when some components are repeated,' Journal of the American Statistical Association, 68, 894-898   DOI
11 Ye, K. and Berger, J. (1991). 'Noninformative priors for inferences in exponential regression models,' Biometrika, 78, 645-656   DOI   ScienceOn
12 Kenneth, V. D., John, S. D., and Kenneth, J. S. (1998). 'Incorporating a geometric mean formula into CPI,' Monthly Labor Review, October, 2-7
13 Cowles, M., and Carlin, B. (1996). 'Markov chain Monte Carlo diagnostics: a comparative review,' Journal of the American Statistical Association, 91, 883-904   DOI   ScienceOn
14 Mukerjee, R. and Reid, N. (1999). 'On a property of probability matching priors: Matching the alternative coverage probabilities,' Biometrika, 86, 333-340   DOI   ScienceOn
15 Datta, G. S. and Ghosh, M., and Mukerjee, R. (2000). 'Some new results on probability matching priors', Calcutta Statistical Association Bulletin, 50, 179-192
16 Chen, M. H., Shao, Q. M. (1999). 'Monte Carlo estimation of Bayesian credible and HPD intervals.' Journal of Computational and Graphical Statistics, 8, 69-92   DOI   ScienceOn
17 Lehmann, E. L. (1959). Testing Statistical Hypotheses, John Wiley & Son, New York
18 Madansky, A. (1965). 'Approximate confidence limits for the reliability of series and parallel systems,' Technometrics, 7, 495-503   DOI   ScienceOn