Communications for Statistical Applications and Methods

  • 제24권2호
  • /
  • Pages.129-142
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  • 2017
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Closeness of Lindley distribution to Weibull and gamma distributions

  • Raqab, Mohammad Z. (Department of Statistics and Operations Research, Kuwait University) ;
  • Al-Jarallah, Reem A. (Department of Statistics and Operations Research, Kuwait University) ;
  • Al-Mutairi, Dhaifallah K. (Department of Statistics and Operations Research, Kuwait University)
  • 투고 : 2016.10.21
  • 심사 : 2017.02.18
  • 발행 : 2017.03.31
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초록

In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

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참고문헌

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