• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.933-943
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• 2006

For multiply Type-II censored samples from two-parameter Rayleigh distribution, we derive some approximate maximum likelihood estimators of parameter in the Rayleigh distribution when the other parameter is known. We also compare the proposed estimators in the sense of the mean squared error for various censored samples.

• Journal of the Korean Data and Information Science Society
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• 제9권1호
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• pp.71-76
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• 1998

By assuming a general progressive Type-II censored sample, we propose the minimum risk estimator (MRE) of the location parameter and the scale parameter of the two-parameter exponential distribution. An example is given to illustrate the methods of estimation discussed in this paper.

• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.817-826
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• 2007

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the location parameter in a generalized extreme value distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• 품질경영학회지
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• 제26권1호
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• pp.161-171
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• 1998

Kim and Kim (1997) developed a method of estimating the mean lifetime based on the augmented data after imputing censored observations. Assuming the linear relationship between lifetime and covariates, and then introducing the procedure of Buckley and James (1979) to estimate the mean lifetimes of censored observations, they proposed a mean lifetime estimator and its consistency under the regularity conditions. In this article, the Kim and Kim's estimator is compared with the estimator introduced by Gill (1983) through simulations under the various configurations. Also, their estimator is illustrated with two real data sets.

• Communications for Statistical Applications and Methods
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• 제19권5호
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• pp.697-704
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• 2012

The maximum likelihood(ML) estimation of the scale parameters of an exponential distribution based on progressive Type II censored samples is given. The sample is multiply censored (some middle observations being censored); however, the ML method does not admit explicit solutions. In this paper, we propose multiply progressive Type II censoring. This paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply progressive Type II censoring. The scale parameter is estimated by approximate ML methods that use two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator(MLE) of the scale parameter under the proposed multiply progressive Type II censored samples. We compare the estimators in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20 and 40 and various censored schemes. The $AMLE_{II}$ is better than MLE and $AMLE_I$ in the sense of the MSE.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.791-800
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• 1999

Gross and Lai(1996) proposed a new approach for ordinary regression with left-truncated and right-censored (I.t.r.c) data. This paper shows how to apply nonparametric algorithms such as multivariate adaptive regression splines to 1.t.r.c data.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.191-203
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• 2019

The problem of examining how well an assumed distribution fits the data of a sample is of significant and must be examined prior to any inferential process. The observed failure time data of items are often not wholly available in reliability and life-testing studies. Lowering the expense and period associated with tests is important in statistical tests with censored data. Goodness-of-fit tests for perfect data can no longer be used when the observed failure time data are progressive Type II censored (PC) data. Therefore, we propose goodness-of-fit test statistics and a graphical method based on generalized Lorenz curve for PC data from a location-scale distribution. The power of the proposed tests is then assessed through Monte Carlo simulations. Finally, we analyzed two real data set for illustrative purposes.

• 응용통계연구
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• 제13권2호
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• pp.427-436
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• 2000

이 논문에서는 신뢰수명자료의 분석에 많이 사용되는 지수분포, 와이블분포, 로그정규분포에 대해, 현재의 자료가 어느 분포에 가장 적합한가를 알아보기 위한 베이자안 모형 선택방법을 제안한다. 일반적으로, 모수에 대한 사전분포가 부적절 분포인 경우, 베이즈 요인(Bayes factor)은 미지의 상수를 포함한다. 이러한 문제점을 해결하기 위하여 O’Hagan(1995)에 의해 제안된 fractional Bayes factor를 이용하여 자료를 가장 적합시키는 모형을 찾는다. 특히, 제2종 중도절단자료가 주어진 경우. 이 자료를 이용한 베이지안 모형선택에 대한 연구는 거의 이루어진 바가 없다. 실제 자료와 인위적인 자료를 이용하여 로그정규분포, 지수분포, 와이블모형중 어느 모형에 가장 잘 적합한지를 검정하는 예를 보인다.

• 한국자동차공학회논문집
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• 제18권1호
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• pp.31-36
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• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2006년도 추계학술대회
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• pp.327-336
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• 2006

The odds ratio is used for assessing the disease-exposure association, because epidemiological data for case-control of cohort studies are often summarized into 2 ${\times}$ 2 tables. In this paper we define the odds ratio function(ORF) that extends odds ratio used on discrete survival event data to continuous survival time data and propose estimation procedures with censored data. The first one is a nonparametric estimator based on the Nelson-Aalen estimator of comulative hazard function, and the others are obtained using the concept of empirical odds ratio. Asymptotic properties such as consistency and weak convergence results are also provided. The ORF provides a simple interpretation and is comparable to survival function or comulative hazard function in comparing two groups. The mean square errors are investigated via Monte Carlo simulation. The result are finally illustrated using the Melanoma data.