• Title/Summary/Keyword: Exponential Location Parameters

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Bayesian Test for the Difference of Exponential Guarantee Time Parameters

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1095-1106
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    • 2005
  • When X and Y have independent two parameter exponential distributions, we develop a Bayesian testing procedures for the equality of two location parameters. The reference prior in non-regular exponential model is derived. Under this reference prior, we propose a Bayesian test procedures for the equality of two location parameters using fractional Bayes factor and intrinsic Bayes factor. Simulation study and some real data examples are provided.

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Bayesian Test for the Difference of Exponential Guarantee Time Parameters

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.15-23
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    • 2004
  • When X and Y have independent two parameter exponential distributions, we develop a Bayesian testing procedures for the equality of two location parameters. Under the noninformative prior, we propose a Bayesian test procedures for the equality of two location parameters using fractional Bayes factor and intrinsic Bayes factor. Simulation study and some real data examples are provided.

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Bootstrap and Delete-d Jackknife Confidence Intervals for Parameters of an Exponential Distribution

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.1
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    • pp.59-70
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    • 1997
  • We introduce several estimators of the location and the scale parameters of the two-parameter exponential distribution, and then compare these estimators by the mean square error (MSE). Using the parametric bootstrap estimators and the delete-d jackknife, we obtain the bootstrap and the delete-d jackknife confidence intervals for the location and the scale parameters and compare the bootstrap confidence intervals with the delete-d jackknife confidence intervals by length and coverage probability through Monte Carlo method.

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AMLEs for the Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang Suk-Bok;Lee Sang-Ki
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.603-613
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    • 2005
  • We propose some estimators of the location parameter and derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter in the exponential distribution based on multiply Type-II censored samples. We calculate the moments for the proposed estimators of the location parameter, and the AMLEs which are the linear functions of the order statistics. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

Estimation for a bivariate survival model based on exponential distributions with a location parameter

  • Hong, Yeon Woong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.921-929
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    • 2014
  • A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

Confidence Intervals and Joint Confidence Regions for the Two-Parameter Exponential Distribution based on Records

  • Asgharzadeh, A.;Abdi, M.
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.103-110
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    • 2011
  • Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.

Approximate MLEs for Exponential Distribution Under Multiple Type-II Censoring

  • Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.983-988
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    • 2003
  • When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two-parameter exponential distribution do not admit explicitly. In this case, we propose some approximate maximum likelihood estimators by approximating the likelihood equations appropriately. We present an example to illustrate these estimation methods.

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Bayesian Estimation for the Left Truncated Exponential Lifetime Distribution with Inclusion and Exclusion of an Outlier

  • PARK, Man-Gon
    • Journal of Korean Society for Quality Management
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    • v.16 no.2
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    • pp.56-67
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    • 1988
  • It is wellknown that the left truncated exponential distribution with positivity constraint on the location parameter is appropriate as a lifetime distribution model, In this paper, some Bayes estimators of the parameters and reliability for the left truncated exponential lifetime distribution when an unidentified-failure outlier is included and it is excluded in the exchangeable outlier model are proposed, and the performances of these proposed Bayes estimators are also discussed.

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Estimation for the Skewed Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Han, Jun-Tae;Park, Sun-Mi
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.10a
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    • pp.125-133
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    • 2004
  • In this paper, we derive the approximate maximum likelihood estimators of the scale and location parameters of the skewed exponential distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

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