• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.49-56
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• 2001

In this paper we consider empirical Bayes estimation of the hazard rate and survival probabilities with right censored data under the assumption that the hazard function is constant over the period of observation and the prior distribution is gamma. We provide an estimator of the first derivative of the prior moment generating function that converges at each point to the true value in $L_2$ and use it to obtain, easy to compute, asymptotically optimal estimators under the squared error loss function.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.357-370
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• 2022

In this paper, Tobit and Heckit models are introduced. These models have been used for analyzing censored data. Censoring occurs at a specific point and a large number of observations are distributed with a positive probability at a certain point. Censoring can occur due to observing limitation or exogenous variables. Tobit and Heckit models are used to correct sample selection bias, which can occur when an ordinary linear regression model is fitted to censored data. However, the difference between the two models is not clearly accounted for; hence, they have often been used interchangeably. Therefore, the suitability of the models was validated through simulated data, and demonstrated through real data. As the result, it was confirmed that both Tobit and Heckit models are well-fitted to the data censored due to observing limitation, although Tobit model was fitted parsimoniously. In contrast, only Heckit model is well-fitted to the data censored due to exogenous variables.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.195-209
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• 2014

In this paper, we derive the estimators of the location parameter and the scale parameter in a logistic distribution based on multiply type-II censored samples by the approximate maximum likelihood estimation method. We use four modified empirical distribution function (EDF) types test for the logistic distribution based on multiply type-II censored samples using proposed approximate maximum likelihood estimators. We also propose the modified normalized sample Lorenz curve plot for the logistic distribution based on multiply type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.961-969
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• 2009

A hybrid censoring is a mixture of Type-I and Type-II censoring schemes. This paper deals with estimation based on Type-I hybrid censored samples from the half triangle distribution. We derive some estimators of the scale parameter of the half triangle distribution based on Type-I hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1167-1177
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• 2017

The censored regression using the pseudo-response variable proposed by Buckley and James has been one of the most well-known models. Recently, the varying coefficient regression model has received a great deal of attention as an important tool for modeling. In this paper we propose a censored varying coefficient regression model using Buckley-James method to consider situations where the regression coefficients of the model are not constant but change as the smoothing variables change. By using the formulation of least squares support vector machine (LS-SVM), the coefficient estimators of the proposed model can be easily obtained from simple linear equations. Furthermore, a generalized cross validation function can be easily derived. In this paper, we evaluated the proposed method and demonstrated the adequacy through simulate data sets and real data sets.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.569-575
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• 2018

Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.46-56
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• 1983

An algorithm based on EM procedure which finds maximum likelihood estimators in a nonlinear regression with censored data is proposed, and asymptotic properties of the estimator are investigated in detail. Some numerical examples are also given.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1526-1530
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• 2007

In this study, the chukwookee data were evaluated by applying that for the historical rainfall frequency analysis. To derive a two parameter log-normal distribution by using historical data and modern data, censored data MLE and binomial censored data MLE were applied. As a result, we found that both average and standard deviation were all estimated smaller with chukwookee data then those with only modern data. This indicates that rather big events rarely happens during the period of chukwookee data then during the modern period. The frequency analysis results using the parameters estimated were also similar to those expected. The point to be noticed is that the rainfall quantiles estimated by both methods were similar, especially for the 99% threshold. This result indicates that the historical document records like the annals of Chosun dynasty could be valuable and effective for the frequency analysis. This also means the extension of data available for frequency analysis.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.59-68
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• 2005

We consider the problem of estimating the scale and shape parameter of the Weibull distribution based on censored samples. we propose the approximate maximum likelihood estimators (AMLEs) of the scale and shape parameters in the Weibull distribution based on Type-II censored samples. We compare the proposed estimators in the sense of mean squared error (MSE).