• Title/Summary/Keyword: Distribution Information

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Large Sample Tests for Independence and Symmetry in the Bivariate Weibull Model under Random Censorship

  • Cho, Jang-Sik;Ko, Jeong-Hwan;Kang, Sang-Kil
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.405-412
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    • 2003
  • In this paper, we consider two components system which the lifetimes have a bivariate weibull distribution with random censored data. Here the censoring time is independent of the lifetimes of the components. We construct large sample tests for independence and symmetry between two-components based on maximum likelihood estimators and the natural estimators. Also we present a numerical study.

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GEOMETRICAL PROPERTIES OF t-DISTRIBUTION

  • CHO, BONG SIK;BAEK, HOH YOO
    • Honam Mathematical Journal
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    • v.28 no.3
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    • pp.433-438
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    • 2006
  • The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, the parameter space of the t-distribution using its Fisher's matrix is defined. The Riemannian and scalar curvatures to parameter space are calculated.

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A Study on the Key Distribution Protocol for Secure P2P information Security Service (안전한 P2P 정보보호 서비스를 위한 키 분배 프로토콜에 관한 연구)

  • Lee, Jun Seok
    • Journal of Industrial Convergence
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    • v.6 no.1
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    • pp.57-72
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    • 2008
  • In this study, general outline of P2P(peer to peer) application was analyzed dealing with security attacks and threats on the P2P environment. Information security service was studied to provide secure P2P service under the information threats. This study proposes two methods to provide secure information security service. One is a method to use personal firewall software on the peer. The other is a method to use key distribution protocol for confidentiality and integrity.

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Integral constants of Transformed geometric Poisson process

  • Park, Jeong-Hyun
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.305-310
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    • 1998
  • In this paper, we introduce the conditions that the P-process has the intensity function which it is a standard form of gamma distribution. And we show that the transformed geometric Poisson process which the intensity function is a standard form of gamma distribution is a alternative sign P-process

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On Jacknife Reliability Estimation in the Weibull Case

  • Lee, In-Suk;Keum, Yoon-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.39-44
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    • 2002
  • We compare MISE of the MLE, UMVUE, invariantly optimal estimator and Jacknife estimator for the reliability function of the Weibull distribution when the sample size is small.

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Recurrence Relations in the Transformed Exponential Distributions

  • Choi, Jeen-Kap;Mo, Kap-Jong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.1031-1044
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    • 2003
  • In this paper, we establish some recurrence relations of the moments, product moments, percentage points, and modes of order statistics from the transformed exponential distribution.

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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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Test for the Presence of Seasonality in Time Series Models

  • Lee, Sung-Duck
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.1
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    • pp.71-78
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    • 2001
  • Three test statistics are proposed for the presence of seasonality in multiplicative seasonal time series models. Further their common limiting distribution is derived under some assumptions.

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