• Title/Summary/Keyword: censoring data

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Parametric Empirical Bayes Estimators with Item-Censored Data

  • Choi, Dal-Woo
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.261-270
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    • 1997
  • This paper is proposed the parametric empirical Bayes(EB) confidence intervals which corrects the deficiencies in the naive EB confidence intervals of the scale parameter in the Weibull distribution under item-censoring scheme. In this case, the bootstrap EB confidence intervals are obtained by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive EB confidence intervals through Monte Carlo study are also presented.

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Regression Quantile Estimations on Censored Survival Data

  • Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.31-38
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    • 2002
  • In the case of multiple survival times which might be censored at each covariate vector, we study the regression quantile estimations in this paper. The estimations are based on the empirical distribution functions of the censored times and the sample quantiles of the observed survival times at each covariate vector and the weighted least square method is applied for the estimation of the regression quantile. The estimators are shown to be asymptotically normally distributed under some regularity conditions.

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Robust Regression and Stratified Residuals for Left-Truncated and Right-Censored Data

  • Kim, Chul-Ki
    • Journal of the Korean Statistical Society
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    • v.26 no.3
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    • pp.333-354
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    • 1997
  • Computational algorithms to calculate M-estimators and rank estimators of regression parameters from left-truncated and right-censored data are developed herein. In the case of M-estimators, new statistical methods are also introduced to incorporate leverage assements and concomitant scale estimation in the presence of left truncation and right censoring on the observed response. Furthermore, graphical methods to examine the residuals from these data are presented. Two real data sets are used for illustration.

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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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    • v.15 no.2
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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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The Study for Software Future Forecasting Failure Time Using Time Series Analysis. (시계열 분석을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.11 no.3
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    • pp.19-24
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    • 2011
  • Software failure time presented in the literature exhibit either constant monotonic increasing or monotonic decreasing, For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

The Study for Software Future Forecasting Failure Time Using Curve Regression Analysis (곡선 회귀모형을 이용한 소프트웨어 미래 고장 시간 예측에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.12 no.3
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    • pp.115-121
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    • 2012
  • Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

Bayesian and maximum likelihood estimations from exponentiated log-logistic distribution based on progressive type-II censoring under balanced loss functions

  • Chung, Younshik;Oh, Yeongju
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.425-445
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    • 2021
  • A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.

Testing Whether Failure Rate Changes its Trend Using Censored Data

  • Jeong, Hai-Sung;Na, Myung-Hwan;Kim, Jae-Joo
    • International Journal of Reliability and Applications
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    • v.1 no.2
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    • pp.115-121
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    • 2000
  • The trend change in aging properties, such as failure rate and mean residual life, of a life distribution is important to engineers and reliability analysts. In this paper we develop a test statistic for testing whether or not the failure rate changes its trend using censored data. The asymptotic normality of the test statistics is established. We discuss the efficiency values of loss due to censoring.

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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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Optimal Plan for Fully Accelerated Life Tests with Three-Step Stress Under Type I Censoring

  • Moon, Kyoung-Ae;Shin, Im-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.295-299
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    • 1996
  • In this paper, optimal change times are determined for fully three-step stress accelerated life tests, which minimize the asymptotic variance for maximum likelihood estimator of logarithm of the failure rate at the usual condition and exponential distribution is given for life time data.

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