• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2106-2117
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• 2017

An effective statistical feature extraction approach of data sampling of fault in the combined transmission system is presented in this paper. The proposed algorithm leads to high accuracy at minimum cost to predict fault location and fault type classification. This algorithm requires impedance measurement data from one end of the transmission line. Modal decomposition is used to extract positive sequence impedance. Then, the fault signal is decomposed by using discrete wavelet transform. Statistical sampling is used to extract appropriate fault features as benchmark of decomposed signal to train classifier. Support Vector Machine (SVM) is used to illustrate the performance of statistical sampling performance. The overall time of sampling is not exceeding 1 1/4 cycles, taking into account the interval time. The proposed method takes two steps of sampling. The first step takes 3/4 cycle of during-fault and the second step takes 1/4 cycle of post fault impedance. The interval time between the two steps is assumed to be 1/4 cycle. Extensive studies using MATLAB software show accurate fault location estimation and fault type classification of the proposed method. The classifier result is presented and compared with well-established travelling wave methods and the performance of the algorithms are analyzed and discussed.

• 대한수의학회지
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• 제48권3호
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• pp.357-361
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• 2008

Although power analysis is of important tool of research, investigators in veterinary medicine are unaware of the concepts of the statistical power. Two types of error occur in classical hypothesis testing and, those errors should be avoided, if possible. Since power is highly dependent on the sample size, whenever declaring non-statistically significant result they should consider the potential for committing a Type II error in their studies, which refers to the probability of falsely stating that two treatments are equivalent despite true difference between them. Also, sample size determination is one of the most important tasks facing the researcher when planning a diagnostic study, and provides valuable information on the characteristics of a test performance. This type of analysis forms the basis for proper interpretation of test results. The aim of this article was to re-evaluate some selected studies on diagnostic test reported in the domestic veterinary publications to determine the power and necessary sample size for inequality testing to ensure the desired power. Power calculations were illustrated using real-life examples of comparison of a new test and a reference test for detecting antibodies of various animal diseases. Factors affecting to the power were also discussed.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.219-224
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• 2003

Translation errors in the statistical funtions of the Korean Excel 2002 software are analyzed into three categories: Pure translation mistakes; Vague translation; Inconsistent translation. These errors have not been corrected at least for the last ten years and therefore, it is suspicious that the Korean agents for foreign software companies are more interested in marketing with monololy power than in improving quality of their products

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2012년 추계학술대회
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• pp.461-471
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• 2012

Most useful statistical techniques in six sigma DMAIC are hypothesis testing and interval estimation. So this paper reviews and derives sample size formula by considering significance level, power of detectability and effect difference. The quality practioners can effectively interpret the practical and statistical significance with the rational sample sizing.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.353-359
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• 2003

This paper deals with the problem of testing mean change with one change-point with the normal random variables. We propose a test with the mean difference for change in a location parameter. A power comparison study of various change-point test statistics is performed via Monte Carlo simulation with S-plus software.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.283-290
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• 1996

The simulation study shows that the rank transform test has relatively superior power advantages over the parametric analysis of variance test in many cases for a $2^3$ factorial design, particularly with heavy-tailed distributions of the error terms. However the rank transform test should be cautiously used when all main effects and interactions related to a testing effect are possibly present at the same time.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.185-189
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• 2002

본 논문에서는 초 모집단 모형 하에서 HT 추정량의 분산의 하한에 관계된 층화추정량의 효율성에 대해 다루었다. 특별히 Dalenius-Hodges 층화와 표본배분방법 중 멱배분(power allocation)을 적용했을 때 최소분산 성질에 대해 살펴보았다.

• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.707-711
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• 2009

We propose new cointegration tests using signs of the regressors as instrumental variable. Our tests have the asymptotic standard normal distribution and are free from the dimension of regressors under the null hypothesis of no cointegration. A Monte-Carlo simulation shows that the proposed tests have a stable size and an improved power. Particulary, the tests have better power for small numbers of observations.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.97-106
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• 2000

In time series analysis we generally use Box-Cox power transformation for variance stabilization. In this paper we show that order estimator and one step ahead forecast of transformed AR(1) model are approximately invariant to those of the original model under some assumptions. A small Monte-Carlo simulation is performed to support the results.

• Journal of the Korean Statistical Society
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• 제26권4호
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• pp.467-476
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• 1997

The two-sample t-test is not expected to be optimal when the two samples are not drawn from normal populations. According to Box and Cox (1964), the transformation is estimated to enhance the normality of the tranformed data. We investigate the asymptotic relative efficiency of the ordinary t-test versus t-test applied transformation introduced by Yeo and Johnson (1997) under Pitman local alternatives. The theoretical and simulation studies show that two-sample t-test using transformed date gives higher power than ordinary t-test for location-shift models.