• International Journal of Reliability and Applications
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• v.1 no.2
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• pp.155-165
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• 2000

In this paper, we propose some estimators of Kullback- Leibler Information functions using the data from three step stress accelerated life tests. This acceleration model is assumed to be a tampered random variable model. Some asymptotic properties of proposed estimators are proved. Simulations are performed for comparing the small sample properties of the proposed estimators under use condition of accelerated life test.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.951-963
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• 2003

In this paper, we propose goodness of fit test statistics based on the estimated Kullback-Leibler information functions using the data from three step stress accelerated life test. This acceleration model is assumed to be a tampered random variable model. The power of the proposed test under various alternatives is compared with Kolmogorov-Smirnov statistic, Cramer-von Mises statistic and Anderson-Darling statistic.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.923-931
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• 2005

The two parameter generalized exponential distribution was recently introduced by Gupta and Kundu (1999). It is observed that the generalized exponential distribution can be used quite effectively to analyze skewed data set. This paper develops the accelerated life test model using generalized exponential distribution and considers maximum likelihood estimation of parameters under the tampered random variable model. To show the performance of proposed maximum likelihood estimates, some simulation will be performed. Using a real data set, an example will be given.

• Journal of Korean Society for Quality Management
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• v.31 no.4
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• pp.194-202
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• 2003

In this paper, we propose goodness of fit test statistics for exponentiality in accelerated life tests data based on Kullback­Leibler information functions. This acceleration model is assumed to be a tampered random variable model. The procedure is applicable when the exponential parameter using the data from accelerated life tests is or is not specified under null hypothesis. And we compare the power of the proposed test statistics with Kolmogorov­Smirnov, Cramer von Mises and Anderson­Darling statistics in the small sample.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.235-240
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• 2000

In this paper a test of fit for exponentiality and we propose the estimator of Kullback-Leibler Information functions using the data from accelerated life tests. This acceleration model is assumed to be a tampered random variable model. The procedure is applicable when the exponential parameter based on the data from accelerated life tests is or is not specified under null hypothesis. Using Simulations, the power of the proposed test based on use condition of accelerated life test under alternatives is compared with that of other standard tests in the small sample.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.563-573
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• 2000

In this paper, we propose three estimators of Kullback-Leibler Information functions using the data from accelerated life tesb. This acceleration model is assumed to be a tampered random variable model. Some asymptotic properties of proposed estimators are proved. Simulations are performed for comparing the small sample properties of the proposed estimators under use condition of accelerated life test.

• Journal of the Korean Data and Information Science Society
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• v.5 no.2
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• pp.87-94
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• 1994

In this paper, we consider optimum plan to determine stress change times under the three-step stress PALTs, assuming that each test units follows an exponential distribution. The tampered random variable(TRV) model for the three-step stress PALTs setup are introduced, and maximum likelihood estimators(MLEs) of the failure rate and the acceleration factors are obtained. The change times to minimize the generalized asymptotic variance(GAVR) of MLEs of the failure rate and the acceleration factors are proposed for the three-step stress PALTs.