• Title/Summary/Keyword: Marshall-Olkin 모형

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Boostrap testing for independence in Marshall and Olkin's model under random censorship (임의중단된 이변량 지수모형의 독립성에 대한 붓스트랩 검정)

  • 김달호;조길호;조장식
    • The Korean Journal of Applied Statistics
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    • v.9 no.2
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    • pp.13-23
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    • 1996
  • In this paper, we consider the Marshall and Olkin's bivariate exponential model under random censorship for the distribution of failure times of a system with two components. We propose a bootstrap testing procedure for independence and compare the powers of it with other tests via Monte Carlo simulation.

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Inference for Bivariate Exponential Model with Bivariate Random Censored Data (이변량 임의 중단된 이변량지수 모형에 대한 추론)

  • Cho, Jang-Sik;Shin, Im-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.37-45
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    • 1999
  • In this paper, we consider two components system having Marshall-Olkin's bivariate exponential model. For the bivariate random censorship, we obtain maximum likelihood estimators of parameters and system reliability. And we propose the methods of homogeniety and independence tests using asymptotic normality. Also we compute the estimators and p-values of the testings through Monte Carlo simulation.

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이변량 1종 중단된 Marshall-Olkin 모형에서 동일성과 독립성 검정

  • 김희재;조장식
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.557-563
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    • 1997
  • Marshall-Olkin의 이변량 지수모형을 따르는 두개의 부품으로 이루어진 시스템에서, 두 부품의 수명들이 이변량 1종 중단된 자료로 관찰되는 경우, 모수에 대한 최우추정량을 구한다. 그리고 두 부품의 수명에 대한 근사적 독립성과 동일성 검정법을 제안하고 몬테칼로 모의실험을 통하여 검정력을 비교하였다.

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Testing for $P(X_{1}\;<\;X_{2})$ in Bivariate Exponential Model with Censored Data (중단자료를 갖는 이변량 지수 모형에서 $P(X_{1}\;<\;X_{2})$에 대한 검정)

  • Park, Jin-Pyo;Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.143-152
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    • 1997
  • In this paper, we obtain maximum likelihood estimators for $P(X_{1}\;<\;X_{2})$ in the Marshall and Olkin's bivariate exponential model with bivariate censored data. The asymptotic normality of the estimator is derived. Also we propose approximate testing for $P(X_{1}\;<\;X_{2})$ based on the M.L.E. We compare the test powers under vsrious conditions through Monte Carlo simulation.

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The Reliability Estimation of Parallel System in Bivariate Exponential Model : Using Bivariate Type 1 Censored Data (이변량 지수모형에서 병렬시스템의 신뢰도 추정 : 이변량 1종 중단 자료이용)

  • 조장식;김희재
    • Journal of Korean Society for Quality Management
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    • v.25 no.4
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    • pp.79-87
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    • 1997
  • In this paper, we obtain maximum likelihood estimator(MLE) of a parallel system reliability for the Marshall and Olkin's bivariate exponential model with birariate type 1 consored data. The asymptotic normal distribution of the estimator is obtained. Also we construct an a, pp.oximate confidence interval for the reliability based on MLE. We present a numerical study for obtaining MLE and a, pp.oximate confidence interval of the reliability.

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Statistical Estimation for Hazard Function and Process Capability Index under Bivariate Exponential Process (이변량 지수 공정 하에서 위험함수와 공정능력지수에 대한 통계적 추정)

  • Cho, Joong-Jae;Kang, Su-Mook;Park, Byoung-Sun
    • Communications for Statistical Applications and Methods
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    • v.16 no.3
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    • pp.449-461
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    • 2009
  • Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level $Z_{st}$ ave been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on statistical estimation under normal process which may result in unreliable assessments of process performance. In this paper, we consider statistical estimation for bivariate VPCI(Vector-valued Process Capability Index) $C_{pkl}=(C_{pklx},\;C_{pklx})$ under Marshall and Olkin (1967)'s bivariate exponential process. First, we derive some limiting distribution for statistical inference of bivariate VPCI $C_{pkl}$. And we propose two asymptotic normal confidence regions for bivariate VPCI $C_{pkl}$. The proposed method may be very useful under bivariate exponential process. A numerical result based on our proposed method shows to be more reliable.