• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.531-542
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• 2008

The unit root test is the major tool for determining whether we use differencing or detrending to eliminate the trend from time series data. Dickey-Fuller test (Dickey and Fuller, 1979) has the low power of test when the sample size is small or the true coefficient of AR(1) process is almost unit root and the Bayesian unit root test has complicated testing procedure. We propose a new unit root testing procedure, which mixed Bayesian approach with the traditional testing procedure. Using simulation studies, our approach showed locally higher powers than Dickey-Fuller test when the sample size is small or the time series has almost unit root and simpler procedure than Bayesian unit root test procedure. Proposed testing procedure can be applied to the time series data that are not observed as process with unit root.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.707-722
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• 1998

This paper evaluates a new clinical trial designs for low infection rate disease. This type of sparse disease reaction makes the traditional two sample t-test or Wilcoxon rank-sum test inefficient compared to a new test suggested. The new test, which is based solely on the larger changes, is shown to be more effective than existing method by simulation for small samples. However, this test can be shown to be connected to the locally most powerful rank test under certain practical conditions. This design is motivated in testing the treatment effects in periodontal disease research.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.215-230
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• 2016

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1200-1209
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• 2003

In this paper, a unified methodology based on the local stress concept to estimate residual strength of locally thinned pipes. An underlying idea of the proposed methodology is that the local stress in the minimum section for locally thinned pipe is related to the reference stress, popularly used in creep problems. Then the problem remains how to define the reference stress, that is the reference load. Extensive three-dimensional finite element (FE) analyses were performed to simulate full-scale pipe tests conducted for various shapes of wall thinned area under internal pressure and bending moment. Based on these FE results, the reference load is proposed, which is independent of materials. A natural outcome of this method is the maximum load capacity. By comparing with existing test results, it is shown that the reference stress is related to the fracture stress, which in turn can be posed as the fracture criterion of locally thinned pipes. The proposed method is powerful as it can be easily generalised to more complex problems, such as pipe bends and tee-joints.

• Journal of the Korean Statistical Society
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• v.33 no.2
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• pp.149-157
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• 2004

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive processes to determine whether or not a time series is stationary. The proposed tests are robust to the outliers and the heteroscedastic errors, and they have an exact binomial null distribution regardless of the period of seasonality and types of median adjustments. A Monte-Carlo simulation shows that the sign test is locally more powerful than the tests based on ordinary least squares estimator (OLSE) for heavy-tailed and/or heteroscedastic error distributions.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.281-286
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• 2003

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive process to determine whether or not a time series is stationary. The tests have an exact binomial null distribution and are robust to the outliers and the heteroscedastic errors. Monte-Carlo simulation shows that the sign test is locally more powerful than the OLSE-based tests for heavy-tailed and/or heteroscedastic error distributions.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.773-779
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• 2003

Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.