• Title/Summary/Keyword: Distribution Journal

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Estimation for Exponential Distribution under General Progressive Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.239-245
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    • 1997
  • By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) and the approximate maximum likelihood estimator (AMLE) of the scale parameter of the one-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

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AMLE for Normal Distribution under Progressively Censored Samples

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.203-209
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    • 1998
  • By assuming a progressively censored sample, we propose the approximate maximum likelihood estimator (AMLE) of the location nd the scale parameters of the two-parameter normal distribution and obtain the asymptotic variances and covariance of the AMLEs. An example is given to illustrate the methods of estimation discussed in this paper.

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System Reliability From Stress-Strength Relationship in Bivariate Pareto Distribution

  • Cho, Jang-Sik;Cho, Kil-Ho;Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.113-118
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    • 2003
  • In this paper, We assume that strengths of two components system follow a bivariate pareto distribution. And these two components are subjected to a common stress which is independent of the strength of the components. We obtain maximum likelihood estimator(MLE) for the system reliability from stress-strength relationship. Also we derive asymptotic properties of the MLE and present a numerical study.

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Estimation for the Half-Triangle Distribution Based on Progressively Type-II Censored Samples

  • Han, Jun-Tae;Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.3
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    • pp.951-957
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    • 2008
  • We derive some approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator(MLE) of the scale parameter in the half-triangle distribution based on progressively Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also obtain the approximate maximum likelihood estimators of the reliability function using the proposed estimators. We compare the proposed estimators in the sense of the mean squared error.

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Noninformative priors for Pareto distribution

  • Kim, Dal-Ho;Kang, Sang-Gil;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.6
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    • pp.1213-1223
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    • 2009
  • In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jereys' prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order matching prior and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. A real example is also considered.

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Unified Estimations for Parameter Changes in a Generalized Uniform Distribution

  • Kim, Jung-Dae;Lee, Jang-Choon
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.295-305
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    • 2002
  • We shall propose several estimators for the shape and scale parameters in a generalized uniform distribution when both parameters are polynomial of a known exposure level, and obtain expectations and variances for their proposed estimators. And we shall compare numerically efficiencies for the several proposed estimators for the shape and scale parameters in a generalized uniform distribution in the small sample sizes.

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Estimation for the Extreme Value Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.3
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    • pp.629-638
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    • 2005
  • We derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the extreme value 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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Inference on Reliability in an Exponentiated Uniform Distribution

  • Lee, Chang-Soo;Won, Ho-Yon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.507-513
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    • 2006
  • We shall consider an inference of the reliability and an estimation of the right-tail probability in an exponentiated uniform distribution. And we shall compare numerically efficiencies for proposed estimators of the scale parameter and right-tail probability in the small sample sizes.

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A Reliability Analysis on the Fatigue Life Prediction in Carbon/Epoxy Composite Material (Carbon/Epoxy 복합재료의 피로수명예측에 관한 신뢰성 해석)

  • Jang, Seong-Soo
    • Journal of the Korean Society of Industry Convergence
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    • v.10 no.3
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    • pp.143-147
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    • 2007
  • In recents years, the statistical properties has become an important quantity for reliability based design of a component. The effects of the materials and test conditions for parameter estimation in residual strength degradation model are studied in carbon/epoxy laminate. It is shown that the correlation between the experimental results and the theoretical prediction on the fatigue life distribution using the life distribution convergence method is very reasonable.

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Performance Analysis of a Loss Retrial BMAP/PH/N System

  • Kim Che-Soong;Oh Young-Jin
    • Journal of Korea Society of Industrial Information Systems
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    • v.9 no.3
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    • pp.32-37
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    • 2004
  • This paper investigates the mathematical model of multi-server retrial queueing system with the Batch Markovian Arrival Process (BMAP), the Phase type (PH) service distribution and the finite buffer. The sufficient condition for the steady state distribution existence and the algorithm for calculating this distribution are presented. Finally, a formula to solve loss probability in the case of complete admission discipline is derived.

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