The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model


The KIPS Transactions:PartD, Vol. 11, No. 6, pp. 1269-1276, Oct. 2004
10.3745/KIPSTD.2004.11.6.1269,   PDF Download:

Abstract

The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.


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Cite this article
[IEEE Style]
H. C. Kim, S. S. Lee, Y. J. Song, "The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model," The KIPS Transactions:PartD, vol. 11, no. 6, pp. 1269-1276, 2004. DOI: 10.3745/KIPSTD.2004.11.6.1269.

[ACM Style]
Hee Cheul Kim, Sang Sik Lee, and Young Jae Song. 2004. The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model. The KIPS Transactions:PartD, 11, 6, (2004), 1269-1276. DOI: 10.3745/KIPSTD.2004.11.6.1269.