• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.97-107
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• 1999

프로파일 분석은 반복측정 자료를 분석하는데 있어서 널리 사용되는 다변량 분석모형이다. 프로파일 분석에서는 처리 그룹간의 비교와 반응 프로파일의 평행성 검정을 위해서 4가지 검정통계량이 널리 사용되고 있다. 이들 검정통계량은 Wilks의 통계량($\Lambda$), Pillai's Trace 통계량(V), Hotelling-Lawley Trace 통계량(U), Roy's Maximum Root 통계량($\Theta$ )이다. 그 동안 이들 통계량들을 비교하기 위한 여러 연구가 있었지만 주로 일반적인 다변량 분산분석 모형에 근거한 비교였다. 본 논문에서는 자료가 반복측정 자료이고 우리의 관심이 프로파일 분석에 있을 때에 이 4가지 통계량의 비교에 초점을 맞추었다.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.579-591
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• 2022

Functional data is collected in various fields. It is often necessary to test whether there are differences among groups of functional data. In this case, it is not appropriate to explain using the point-wise ANOVA method, and we should present not the point-wise result but the integrated result. Various studies on functional data analysis of variance have been proposed, and recently implemented those methods in the package fdANOVA of R. In this paper, I first explain ANOVA and multivariate ANOVA, then I will introduce various methods of analysis of variance for univariate and multivariate functional data recently proposed. I also describe how to use the R package fdANOVA. This package is used to test equality of weekly temperatures in Seoul and Busan through univariate functional data ANOVA, and to test equality of multivariate functional data corresponding to handwritten images using multivariate function data ANOVA.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1421-1428
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• 2016

This paper concerns the freshness of rice depending on packing materials using MANOVA. Freshness of rice is measured in terms of moisture content and rice flavor. Ordinary paper and charcoal-coated paper are compared as packing materials. Storing places are considered as a block. The bivariate observations of moisture content and the rice flavor are compared using MANOVA for a completely randomized block design. It is observed that there is a significant difference between ordinary paper and charcoal-coated paper. Therefore we apply ANOVA for moisture content and rice flavor, respectively. Significant differences are observed for the moisture content but not for the rice flavor.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.119-131
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• 1995

Based on Monte-Carlo simulation results we propose a robust analysis of variance procedure by utilizing trimmed mean and Winsorized variance. We deal with mainly the one-way classification case. We evaluate the empirical distribution of a pseudo-F statistic based on symmetrically Winsorized sum of squares when the population is normally distributed.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.121-131
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• 1998

이 논문의 목적은 비모수 회귀모형에 있어서의 오차의 분산을 추정하는 방법들 중 차분에 기저한 방법 (difference-based methods)을 이용한 기존의 추정량들을 비교 분석하는데 있다. 특히 점근적인 최적 이차 차분에 기저한 Hall과 Kay, Titterington(1990)의 HKT 추정량에 대한 그들의 추정량에 대한 문제점들을 제시하고, HKT추정량과, GSJS추정량, Rice추정량에 대하여 모의 실험을 이용하여 모수에 대한 수렴 속도를 비교 분석 하였다. 또한 GSJS 추정량에 대한 일치성과 수렴 속도를 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.225-228
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• 2021

동형암호를 이용한 통계 분석은 기존의 개인정보보호 문제로 수행할 수 없었던 데이터에 대해서 통계분석이 가능하게 만든다. 본 논문에서는 대용량 데이터에 사용되는 대표적 통계 수치인 평균, 분산, 왜도, 첨도를 병렬처리를 사용하여 구하는 방법을 제안한다. 또한, 연산이 비교적 제한적인 동형암호에서도 통계적 수치를 구하기 위하여 동형암호문끼리의 뺄셈, 나눗셈, 제곱근 연산을 제안한다. 이를 통해, 분산된 대용량 데이터에 대해서도 동형암호를 통해 다양한 통계 연산이 가능할 것으로 기대된다.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.475-485
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• 2007

In this work we measured and analyzed the subjective opinions of consumers towards the sound quality of car audios through a questionnaire. First of all, we chose eight controllable factors which had been known to affect the quality of reproduced sound. An orthogonal design of experiments was used to imitate the objective sound environments by reproducing the combinations of 8 sound characteristics, each with two levels. Then we defined 8 corresponding response variables to measure the subjective opinions towards the quality of reproduced sound. Finally, we applied the Multivariate Analysis of Valiance to explore the significant sound characteristics which affected the subjective opinions towards the quality of reproduced sound.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.437-445
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• 1999

The present paper describes the problem of hydrologic response estimation using non-parametric ridge regression method. The method adapted in this work is based on the minimization of the $C_L$ statistics, which is an estimate of the mean square prediction error. For this method, effects of using both the identity matrix and the Laplacian matrix were considered. In addition, we evaluated methods for estimating the error variance of the impulse response. As a result of analyzing synthetic and real data, a good estimation was made when the Laplacian matrix for the weighting matrix and the bias corrected estimate for the error variance were used. The method and procedure presented in present paper will play a robust and effective role on separating hydrologic response.

• The Journal of Engineering Geology
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• v.23 no.4
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• pp.353-361
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• 2013

To analyze the distribution of earthquake-induced strain data in rock masses, statistical analysis was performed on four-directional strain data obtained from a ground movement monitoring system installed in Korea. Strain data related to the 2011 Tohoku-oki earthquake and two aftershocks of >M7.0 in 2011 were used in x-MR control chart analysis, a type of univariate statistical analysis that can detect an abnormal distribution. The analysis revealed different dispersion times for each measurement orientation. In a more comprehensive analysis, the strain data were re-evaluated using multivariate statistical analysis (MSA) considering correlations among the various data from the different measurement orientations. $T_2$ and Q-statistics, based on principal component analysis, were used to analyze the time-series strain data in real-time. The procedures were performed with 99.9%, 99.0%, and 95.0% control limits. It is possible to use the MSA data to successfully detect an abnormal distribution caused by earthquakes because the dispersion time using the 99.9% control limit is concurrent with or earlier than that from the x-MR analysis. In addition, the dispersion using the 99.0% and 95.0% control limits detected an abnormal distribution in advance. This finding indicates the potential use of MSA for recognizing abnormal distributions of strain data.