• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.871-881
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• 2011

In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.69-78
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• 1994

We obtain the Bayes estimator(BE), the minimum variance unbiased estimator(MVUE) and maximun likelihood estimator(MLE) of the reliability when the distribution of the stress and the strength are Weibull with known shape parameters. The experiment is terminated before all of the items on the test have failed and the failed items are partially replaced. Performance of the three estimators for moderate size samples are compared through Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.631-638
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• 2008

Accelerated Lifetime Test is a method of estimation of lifetime quality characteristics under operation condition with the accelerated lifetime data obtained under accelerated stress. In this paper we propose estimation method with accelerated lifetime data using quantile regression. We apply the method to real data with Arrhenius and Inverse power model.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.317-325
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• 2010

In this paper, we develop four modified empirical distribution function (EDF) type tests using approximate maximum likelihood estimators for the half-logistic distribution based on multiply Type-II censored samples. We also propose modified normalize sample Lorenz curve polt and new test statistics. We compare the above test statistics in the sense of the power for various censored samples. We present an example to illustrate this method.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.205-217
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• 2006

In this paper, we consider the problem of testing for a change of the parameter function ${\theta}(t)$ that may have a discontinuity at some unknown point ${\tau}$. We introduce a varying-h moving estimate to test the null hypothesis that ${\theta}(t)$ is continuous against the alternative that ${\theta}({\tau}-){\neq}{\theta}({\tau}+)$. Simulation results are provided for illustration.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.99-110
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• 1994

The strength-stress model has been widely used in a variety of areas including testing the reliability of the item or design procedures. This model was first introduced in 1950's and can be found on various applications in civil, aerospace engineering etc. This paper considers the strength-stress model in detail and proposes an estimator which deals with the reliability estimation problem based on censored observations in the strength variables.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.583-594
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• 2021

In this paper, we propose wavelet-based procedures to identify the difference between images, including portraits and handwriting. The proposed methods are based on a novel combination of multiscale methods with a regularization technique. The multiscale method extracts the local characteristics of an image, and the distinct features are obtained through the regularized regression of the local characteristics. The regularized regression approach copes with the high-dimensional problem to build the relation between the local characteristics. Lytle and Yang (2006) introduced the detection method of forged handwriting via wavelets and summary statistics. We expand the scope of their method to the general image and significantly improve the results. We demonstrate the promising empirical evidence of the proposed method through various experiments.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.57-63
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• 2016

The purpose of this study was to raise some questions about the supply and demand statistics of fisheries products and to find implications for food supply and demand. There are three problems in the statistics of fisheries supply and demand. First, it is a structural problem of supply and demand statistics. Supply and demand statistics are not accurate because the feed, the amount of loss, and the waste rate are not surveyed. Second, the amount of fish used as a moist pellet is missing. Third, although some of the seaweed and kelp production is used as abalone feed, it is not classified as feed. Taking these results into consideration, at least 300,000 tons should be classified as feed for fisheries supply and demand statistics. As mentioned above, the current statistics on the supply and demand of fisheries are incomplete and structural improvement is needed.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.139-145
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• 2002

This paper deals with the problem of obtaining the Bayesian predictive density function and the prediction intervals for a future observation and the p-th order statistics of n future observations for the exponential model under the censored sampling with incomplete information.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.433-443
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• 2003

In this study, we provide a comparison of multivariate Q-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus well known to those who study statistics. We can analyze data through the direct Input method(command) in SAS and use of menu method in SPSS, Minitab and S-plus. The analysis performance method is chosen by the high frequency of use. Widely we compare with each Q-techniques form according to input data, input option, statistical chart and statistical output.