• 제목/요약/키워드: Generalized Exponential Distribution

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Parameters Estimators for the Generalized Exponential Distribution

  • Abuammoh, A.;Sarhan, A.M.
    • International Journal of Reliability and Applications
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    • 제8권1호
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    • pp.17-25
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    • 2007
  • Maximum likelihood method is utilized to estimate the two parameters of generalized exponential distribution based on grouped and censored data. This method does not give closed form for the estimates, thus numerical procedure is used. Reliability measures for the generalized exponential distribution are calculated. Testing the goodness of fit for the exponential distribution against the generalized exponential distribution is discussed. Relevant reliability measures of the generalized exponential distributions are also evaluated. A set of real data is employed to illustrate the results given in this paper.

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On the Estimation of Parameters in ALT under Generalized Exponential Distribution

  • Yoon, Sang-Chul
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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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.

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Estimation for Two-Parameter Generalized Exponential Distribution Based on Records

  • Kang, Suk Bok;Seo, Jung In;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • 제20권1호
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    • pp.29-39
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    • 2013
  • This paper derives maximum likelihood estimators (MLEs) and some approximate MLEs (AMLEs) of unknown parameters of the generalized exponential distribution when data are lower record values. We derive approximate Bayes estimators through importance sampling and obtain corresponding Bayes predictive intervals for unknown parameters for lower record values from the generalized exponential distribution. For illustrative purposes, we examine the validity of the proposed estimation method by using real and simulated data.

Power Exponential Distributions

  • Zheng, Shimin;Bae, Sejong;Bartolucci, Alfred A.;Singh, Karan P.
    • International Journal of Reliability and Applications
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    • 제4권3호
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    • pp.97-111
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    • 2003
  • By applying Theorem 2.6.4 (Fang and Zhang, 1990, p.66) the dispersion matrix of a multivariate power exponential (MPE) distribution is derived. It is shown that the MPE and the gamma distributions are related and thus the MPE and chi-square distributions are related. By extending Fang and Xu's Theorem (1987) from the normal distribution to the Univariate Power Exponential (UPE) distribution an explicit expression is derived for calculating the probability of an UPE random variable over an interval. A representation of the characteristic function (c.f.) for an UPE distribution is given. Based on the MPE distribution the probability density functions of the generalized non-central chi-square, the generalized non-central t, and the generalized non-central F distributions are derived.

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Bayesian estimation for the exponential distribution based on generalized multiply Type-II hybrid censoring

  • Jeon, Young Eun;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • 제27권4호
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    • pp.413-430
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    • 2020
  • The multiply Type-II hybrid censoring scheme is disadvantaged by an experiment time that is too long. To overcome this limitation, we propose a generalized multiply Type-II hybrid censoring scheme. Some estimators of the scale parameter of the exponential distribution are derived under a generalized multiply Type-II hybrid censoring scheme. First, the maximum likelihood estimator of the scale parameter of the exponential distribution is obtained under the proposed censoring scheme. Second, we obtain the Bayes estimators under different loss functions with a noninformative prior and an informative prior. We approximate the Bayes estimators by Lindleys approximation and the Tierney-Kadane method since the posterior distributions obtained by the two priors are complicated. In addition, the Bayes estimators are obtained by using the Markov Chain Monte Carlo samples. Finally, all proposed estimators are compared in the sense of the mean squared error through the Monte Carlo simulation and applied to real data.

RECURRENCE RELATIONS FOR QUOTIENT MOMENTS OF GENERALIZED PARETO DISTRIBUTION BASED ON GENERALIZED ORDER STATISTICS AND CHARACTERIZATION

  • Kumar, Devendra
    • 충청수학회지
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    • 제27권3호
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    • pp.347-361
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    • 2014
  • Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distribution includes exponential distribution, Pareto or Lomax distribution. In this paper, we established exact expressions and recurrence relations satised by the quotient moments of generalized order statistics for a generalized Pareto distribution. Further the results for quotient moments of order statistics and records are deduced from the relations obtained and a theorem for characterizing this distribution is presented.

Optimal designing of skip lot sampling plan of type SkSP-2 with double sampling plan as the reference plan under generalized exponential distribution

  • Suresh, K.K.;Kavithamani, M.
    • International Journal of Reliability and Applications
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    • 제15권2호
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    • pp.77-84
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    • 2014
  • In this paper, a optimal designing methodology is proposed to determine the parameters for skip-lot sampling plan of type SkSP-2 plan with double sampling plan as reference plan, when the lifetime of the product follows generalized exponential distribution. The two points on the operating characteristic curve approach are used to find the optimal parameters for the proposed plan. The plan parameters are determined so as to minimize the average sample number subject to satisfying simultaneously both producer and consumer risks at the acceptable and limiting quality levels respectively.

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Objective Bayesian multiple hypothesis testing for the shape parameter of generalized exponential distribution

  • Lee, Woo Dong;Kim, Dal Ho;Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • 제28권1호
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    • pp.217-225
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    • 2017
  • This article deals with the problem of multiple hypothesis testing for the shape parameter in the generalized exponential distribution. We propose Bayesian hypothesis testing procedures for multiple hypotheses of the shape parameter with the noninformative prior. The Bayes factor with the noninformative prior is not well defined. The reason is that the most of the noninformative prior can be improper. Therefore we study the default Bayesian multiple hypothesis testing methods using the fractional and intrinsic Bayes factors with the reference priors. Simulation study is performed and an example is given.

ON RELATIONS FOR QUOTIENT MOMENTS OF THE GENERALIZED PARETO DISTRIBUTION BASED ON RECORD VALUES AND A CHARACTERIZATION

  • Kumar, Devendra
    • Journal of applied mathematics & informatics
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    • 제31권3_4호
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    • pp.327-336
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    • 2013
  • Generalized Pareto distributions play an important role in re-liability, extreme value theory, and other branches of applied probability and statistics. This family of distribution includes exponential distribution, Pareto distribution, and Power distribution. In this paper we establish some recurrences relations satisfied by the quotient moments of the upper record values from the generalized Pareto distribution. Further a char-acterization of this distribution based on recurrence relations of quotient moments of record values is presented.

An approximate maximum likelihood estimator in a weighted exponential distribution

  • Lee, Jang-Choon;Lee, Chang-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제23권1호
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    • pp.219-225
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    • 2012
  • We derive approximate maximum likelihood estimators of two parameters in a weighted exponential distribution, and derive the density function for the ratio Y=(X+Y) of two independent weighted exponential random variables X and Y, and then observe the skewness of the ratio density.