• 제목/요약/키워드: Random Censoring

검색결과 50건 처리시간 0.024초

A Study on the Conditional Survival Function with Random Censored Data

  • Lee, Won-Kee;Song, Myung-Unn
    • Journal of the Korean Data and Information Science Society
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    • 제15권2호
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    • pp.405-411
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    • 2004
  • In the analysis of cancer data, it is important to make inferences of survival function and to assess the effects of covariates. Cox's proportional hazard model(PHM) and Beran's nonparametric method are generally used to estimate the survival function with covariates. We adjusted the incomplete survival time using the Buckley and James's(1979) pseudo random variables, and then proposed the estimator for the conditional survival function. Also, we carried out the simulation studies to compare the performances of the proposed method.

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Large Sample Test for Independence in the Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.377-383
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    • 2003
  • In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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A Note on Asymptotic Relative Efficiency of the Nonparametric Reliability Estimation for the Proportional Hazards Model

  • Cha, Young-Joon;Lee, Jae-Man;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.173-177
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    • 1998
  • This paper presents the asymptotic relative efficiency of the nonparametric estimator relative to the parametric maximum likelihood estimator of the reliability function under the proportional hazards model of random censorship. Also we examine the efficiency loss due to censoring proportions and misson times.

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A General Mixed Linear Model with Left-Censored Data

  • Ha, Il-Do
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.969-976
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    • 2008
  • Mixed linear models have been widely used in various correlated data including multivariate survival data. In this paper we extend hierarchical-likelihood(h-likelihood) approach for mixed linear models with right censored data to that for left censored data. We also allow a general random-effect structure and propose the estimation procedure. The proposed method is illustrated using a numerical data set and is also compared with marginal likelihood method.

Nonparametric Estimation of the Bivariate Survival Function under Koziol-Green Model I

  • Ahn, Choon-Mo;Park, Sang-Gue
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.975-982
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    • 2003
  • In this paper we considered the problem of estimating the bivariate survival distribution of the random vector (X, Y) when Y may be subject to random censoring but X is always uncensored. Adapting conditional Koziol-Green model, simplified estimator for bivariate survival function is proposed. We perform simulation to compare the proposed estimator with popular estimators and discussed the performance of it.

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Test for Independence in Bivariate Pareto Model with Bivariate Random Censored Data

  • Cho, Jang-Sik;Kwon, Yong-Man;Choi, Seung-Bae
    • Journal of the Korean Data and Information Science Society
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    • 제15권1호
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    • pp.31-39
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    • 2004
  • In this paper, we consider two components system which the lifetimes follow bivariate pareto model with bivariate random censored data. We assume that the censoring times are independent of the lifetimes of the two components. We develop large sample test for testing independence between two components. Also we present a simulation study which is the test based on asymptotic normal distribution in testing independence.

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Reliability for Series System in Bivariate Weibull Model under Bivariate Random Censorship

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제15권1호
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    • pp.219-226
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    • 2004
  • In this paper, we consider two-components system which the lifetimes have a bivariate Weibull distribution with bivariate random censored data. Here the bivariate censoring times are independent of the lifetimes of the components. We obtain estimators and approximated confidence intervals for the reliability of series system based on likelihood function and relative frequency, respectively. Also we present a numerical study.

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A Study of Bayesian and Empirical Bayesian Prediction Analysis for the Rayleigh Model under the Random Censoring

  • Ko, Jeong-Hwan
    • Journal of the Korean Data and Information Science Society
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    • 제6권1호
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    • pp.53-61
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    • 1995
  • This paper deals with problems of predicting, based on the random censored sampling, a future observation and the p-th order statistic of n' future observations for the Rayleigh model. We consider the prediction intervals for the Rayleigh model with respect to an inverse gamma prior distribution. In additions, numerical examples are given in order to illustrate the proposed predictive procedure.

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스트레스함수가 균등분포인 가속수명시험 (Accelerated Life Tests under Uniform Stress Distribution)

  • 원영철
    • 대한안전경영과학회지
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    • 제2권2호
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    • pp.71-83
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    • 2000
  • This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, $S_j$, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, ,$theta_j$, is the random variable of environments and the function of probabilistic stress. Also it is assumed that the general stress distribution is uniform, the life distribution for the given hazard rate, $\theta$, is exponential and inverse power law model holds. In this paper, we obtained maximum likelihood estimators of model parameters and the mean life in use stress condition.

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생존자료분석을 위한 혼합효과 최소제곱 서포트벡터기계 (Mixed effects least squares support vector machine for survival data analysis)

  • 황창하;심주용
    • Journal of the Korean Data and Information Science Society
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    • 제23권4호
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    • pp.739-748
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    • 2012
  • 최소제곱 서포트벡터기계 (least squares support vector machine)는 분류 및 비선형 회귀분석에서 유용하게 사용되고 있는 통계적 기법이다. 본 논문에서는 각 집단별로 생존자료가 관측된 경우 적용할 수 있는 LS-SVM을 제안한다. 제안된 모형은 임의우측 중도절단자료를 비선형 회귀모형에 적용할 수 있게 Kaplan- Meier의 중도절단분포의 추정값을 이용하여 구해진 가중값을 사용하고, 집단 간의 변동을 나타내기 위하여 임의효과항을 포함한다. 벌칙상수와 커널모수의 최적값을 구하기 위하여 일반화 교차타당성함수가 사용되고 모의실험에서는 임의효과항을 포함하지 않은 LS-SVM과 성능을 비교함으로써 제안된 방법의 우수성을 보이기로 한다.