• Journal of the Korean Statistical Society
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• v.3 no.1
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• pp.3-12
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• 1974

The two-stage sequential test, suggested by Baker [2] for testing hypotheses $H_0:\mu=\mu_0$ and $H_1:\mu=\mu_1$ of $N(\mu,\sigma^2)$ with the unknown $\sigma^2$ would not be amenable for applications unles some cluses on the choice of the first-stage sample size are available. The study in this paper is intended to shed some light on the size of the first-stage sample. An approximate method is used to estimate an optimal initial sample size that minimizes the average sample number. In brief, the optimal size is a strictly monotone decreasing function of the quantity $(\mu_1-\mu_0)/\sigma$. Empirical and simulation results are used to ascertain the negligible effect of possible errors due to approximations and assumptions used.

• The Korean Journal of Financial Management
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• v.26 no.2
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• pp.181-201
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• 2009

This study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark. American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample. As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn't beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.31-39
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• 2004

In this paper, we consider two components system which the lifetimes follow bivariate pareto model with bivariate random censored data. We assume that the censoring times are independent of the lifetimes of the two components. We develop large sample test for testing independence between two components. Also we present a simulation study which is the test based on asymptotic normal distribution in testing independence.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1121-1124
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• 2004

Aging test to estimate life property of polymer insulator is executed through several international standard such as IEC 61109 and CEA tracking wheel test, but is not getting clear conclusion yet. There are two methods in the diagnosis method of polymer insulator such as off-line and on-line. The diagnosis methods in off-line are external condition analysis by the eye, contaminant analysis on surface, surface analysis, pollution withstand voltage test, power frequency flashover voltage test, lightning impulse flashover test, tensile fracture load test and flexural load test. The diagnosis methods in off-line most are the method for virgin and last aged sample. However, the diagnosis method in on-line is method that can be evaluate sample state as progressing continuously aging test in beginning, The diagnosis method in on-line is arranged as following: leakage current measurement, electric field, surface state investigation, thermal image, emitting light measurement and then so. In this paper, the tracking performance of polymer insulator with salt solution which is added surface active agent. The diagnosis of insulator sample has been analyzed by leakage current and visual examination.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.926-931
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• 2008

This paper show two different standardized test methods(Japanese Geotechnical Society; JGS 2003). One test is a "Test Method for Frost Heave Prediction Test, JGS 0171-2003", and the other test is a "Test Method for Frost Susceptibility, JGS 0172-2003". The purpose of this test is to obtain the freezing rate(freezing speed), frost heave ratio(heave to sample height), frost heave rate(heaving speed), and other parameters to be used for frost heave prediction and determine the frost susceptibility by freezing test with water intake. This method shall be used to predict the frost heave in frozen ground and evaluate the frost susceptibility of natural and replacement materials.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1047-1057
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• 2009

The nonparametric bivariate two-sample test of Bennett (1967) is extended to the multivariate k sample test. This test has been easily modified for a monotone trend among k samples. Often in applications it is important to consider a set of multivariate response variables simultaneously, rather than individually, and also important to consider testing k samples altogether. Different approaches of estimating the null covariance matrices of the test statistics resulted in the same limiting form. The multivariate k sample test is applied to the non-normal data of a randomized trial conducted for a period of four weeks in mental hospitals. The purpose of the trial is to compare the efficacy of three different interventions for a relief of the frequently occurring problems of constipation, caused as a side effect of antipsychotic drugs during hospitalization. The bowel movement status of patient for a week is summarized into a single severity score, and severity scores of four weeks comprise a four-dimensional multivariate variable. It is desirable with this trial data to consider a multivariate testing among k samples.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.213-224
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• 1994

A diagnostic method useful for detecting outliers in testing the equality of two covariance metrics is developed using the influence curve approach. This method is easily generalized to more than two covariance matrices. A sample version for the influence measure of detecting outliers is considered based on the empirical distribution functions. The sample version includes as its component terms the well-known test statistic for detecting one outlier at a time introduced by Wilks and its generalization to the two-group case.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.789-797
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• 2003

In this paper, we consider two components system which have bivariate weibull model with bivariate random censored data. We proposed large sample test for independence based on maximum likelihood estimator and relative frequency estimator, respectively. Also we derive asymptotic properties for the large sample tests and present a numerical study.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.89-98
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• 2010

In this paper, a two-stage group sampling plan based on the time truncated life test is proposed for the Weibull distribution. The design parameters such as the number of groups and the acceptance number in each stage are determined by satisfying the producer's and consumer's risks simultaneously when the group size and the test duration are specified. The acceptable reliability level is expressed by the ratio of the true mean life to the specified life. It was demonstrated from the comparison with single-stage group sampling plans that the proposed plan can reduce the average sample number or improve the operating characteristics.

• International Journal of Reliability and Applications
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• v.6 no.1
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• pp.53-64
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• 2005

In this paper, we propose a nonparametric test procedure for the multivariate, grouped and right censored data for two sample problem. For the construction of the test statistic, we use the linear rank statistics for each component and apply the permutation principle for obtaining the null distribution. For the large sample case, the asymptotic distribution is derived under the null hypothesis with the additional assumption that two censoring distributions are also equal. Finally, we illustrate our procedure with an example and discuss some concluding remarks. In appendices, we derive the expression of the covariance matrix and prove the asymptotic distribution.