• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.151-159
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• 2021

In this article, our interest is to estimate the association between consecutive gap times which are subject to interval censoring. Such data are referred as doubly interval censored data (Sun, 2006). In a context of serial event, an induced dependent censoring frequently occurs, resulting in biased estimates. In this study, our goal is to propose a Kendall's 𝜏 based association measure for doubly interval censored data. For adjusting the impact of induced dependent censoring, the inverse probability censoring weighting (IPCW) technique is implemented. Furthermore, a multiple imputation technique is applied to recover unknown failure times owing to interval censoring. Simulation studies demonstrate that the suggested association estimator performs well with moderate sample sizes. The proposed method is applied to a dataset of children's dental records.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.441-448
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• 2006

If the completely observed data are assumed to have full information, the censoring causes the loss of information. Previous studies have introduced the indices of information loss via measuring relative changes between the data with censoring and without censoring. In this paper, the comparisons are made for the information loss between type I and type II censoring in two sample problems.

• Journal of Applied Reliability
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• v.2 no.2
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• pp.121-133
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• 2002

This paper concerns informative censoring and some of the difficulties it creates in analysis of survival data. For analyzing censored data, misclassification of informative censoring into random censoring is often unavoidable. It is worthwhile to investigate the impact of neglecting informative censoring on the estimation of the parameters of the proportional hazards model. The proposed model includes a primary failure which can be censored informatively or randomly and a followup failure which may be censored randomly. Simulation shows that the loss is about 30% with regard to the confidence interval if we neglect the informative censoring.

• International Journal of Reliability and Applications
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• v.3 no.1
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• pp.51-60
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• 2002

This paper presents the methodology for obtaining point and interval estimating of the parameters of a new two-parameter distribution with multiple-censored and singly censored data (Type-I censoring or Type-II censoring) as well as complete data, using the maximum likelihood method. The basis is the likelihood expression for multiple-censored data. Furthermore, this model can be extended to a three-parameter distribution that is added a scale parameter. Then, the parameter estimation can be obtained by the graphical estimation on probability plot.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.807-818
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• 2005

In this paper we propose an estimation method for regression quantiles with left-truncated and right-censored data. The estimation procedure is based on the weight determined by the Kaplan-Meier estimate of the distribution of the response. We show how the proposed regression quantile estimators perform through analyses of Stanford heart transplant data and AIDS incubation data. We also investigate the effect of censoring on regression quantiles through simulation study.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.393-401
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• 2012

This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.421-444
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• 1994

Reliability acceptance sampling is concerned with whether to accept or reject a collection of items based upon the information obtained from life testing. Although various reliability acceptance sampling plans have been developed, little is known about their relatvie performances. This paper compares reliability acceptance sampling plans under Type II censoring, Hybrid censoring, and Time-Truncated Type II censoring assuming that the lifetimes of items in a lot follow an exponential distribution. The three plans are compared in terms of the power, the expected number of failures, and the expected time required to reach a decision. Computational experiments are conducted and the results are tabulated to provide guidelines for selecting an appropriate plan for a given situation.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.241-250
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• 2016

In this paper, we consider statistical inferences on the estimation of the parameters of a Weibull distribution when data are randomly censored. Maximum likelihood estimators (MLEs) and approximate MLEs are derived to estimate the parameters. We consider two cases for the censoring model: the assumption that the censoring distribution does not involve any parameters of interest and a censoring distribution that follows a Weibull distribution. A simulation study is conducted to compare the performances of the estimators. The result shows that the MLEs and the approximate MLEs are similar in terms of biases and mean square errors; in addition, the assumption of the censoring model has a strong influence on the estimation of scale parameter.

• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.413-430
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• 2020

The multiply Type-II hybrid censoring scheme is disadvantaged by an experiment time that is too long. To overcome this limitation, we propose a generalized multiply Type-II hybrid censoring scheme. Some estimators of the scale parameter of the exponential distribution are derived under a generalized multiply Type-II hybrid censoring scheme. First, the maximum likelihood estimator of the scale parameter of the exponential distribution is obtained under the proposed censoring scheme. Second, we obtain the Bayes estimators under different loss functions with a noninformative prior and an informative prior. We approximate the Bayes estimators by Lindleys approximation and the Tierney-Kadane method since the posterior distributions obtained by the two priors are complicated. In addition, the Bayes estimators are obtained by using the Markov Chain Monte Carlo samples. Finally, all proposed estimators are compared in the sense of the mean squared error through the Monte Carlo simulation and applied to real data.

• Journal of the Korean Data and Information Science Society
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• v.6 no.2
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• pp.65-76
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• 1995

The importance of left truncated and right censoring cases has considered for better information in medical follow-up and engineering life testing studies. We propose some estimation procedure for the mean residual life function with consistency and asymptotic normality on the left truncated and right censoring model. And then, the comparision with Kaplan-Meier estimator ignoring the left truncated effect and the small sample properities are investigated by asymptotic biases and M.S.E.'s thresh Monte Carlo study.