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http://dx.doi.org/10.7465/jkdi.2013.24.4.755

Bayesian parameter estimation and prediction in NHPP software reliability growth model  

Chang, Inhong (Department of Computer Science and Statistics, Chosun University)
Jung, Deokhwan (Department of Computer Science and Statistics, Chosun University)
Lee, Seungwoo (Department of Computer Science and Statistics, Chosun University)
Song, Kwangyoon (Department of Computer Science and Statistics, Chosun University)
Publication Information
Journal of the Korean Data and Information Science Society / v.24, no.4, 2013 , pp. 755-762 More about this Journal
Abstract
In this paper we consider the NHPP software reliability model. And we deal with the maximum likelihood estimation and the Bayesian estimation with conjugate prior for parameter inference in the mean value function of Goel-Okumoto model (1979). The parameter estimates for the proposed model is presented by MLE and Bayes estimator in data set. We compare the predicted number of faults with the actual data set using the proposed mean value function.
Keywords
Bayesian estimate; maximum likelihood estimation; NHPP; posterior distribution; prior distribution; software reliability model; the sum of squared error;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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