• Physical Therapy Korea
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• v.8 no.4
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• pp.31-43
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• 2001

19명의 건강한 성인 남자의 우세팔쪽 위팔두갈래근에서 피로가 생길 때까지 2.4초를 하나의 주기로 팔꿉을 반복적 등장성으로 굽히고 펴서 표면근전도 신호를 얻었다. 처리과정 A 중앙주파수(MDF )는 이 신호의 0.5초 구간을 power spectrum analy sis (PSA)로 계산하였는데 상당량의 잡음이 있었다. 중앙주파수의 잡음 양을 비교하기 위해, 동일한 표면근전도에서 3번까지 신호를 받았다 (2.4초 구간을 PSA로 계산한 처리과정 B, 13 point 로 moving averages한 처리과정 C, digital low pass filter한 처리과정 D). 그리고 나서 그 신호의 주요 주파수 성분을 뽑아내었다. 위의 중앙주파수 자료와 시간간의 회귀직선을 분석하면 초기 중앙주파수, 회귀기울기, 그리고 피로지수와 같은 모수를 얻을 수 있다. 비모수 검정의 하나인 Kendall 기법으로 네 개의 처리과정간의 모수를 비교하였다. 통계결과 잡음이 처리과정 A보다 B, C, D에서 적었고, D에서 가장 적게 나타났다. 중앙주파수를 digital low pass로 여과(filtering)함으로써 앞으로 있게 될 동적 운동 시 근피로 모니터기의 신뢰도를 높일 수 있다.

• Journal of Soil and Groundwater Environment
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• v.11 no.2
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• pp.56-67
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• 2006

Trends of variation in groundwater levels, electrical conductivities and water temperatures obtained from the national groundwater monitoring stations (95 shallow and 169 deep wells) of Korea were evaluated. For the analysis, both parametric (linear regression) and non-parametric (Mann-Kendall test, Sen's test) methods were adopted. Results of linear regression analysis indicated that about 50% of the monitoring wells showed increasing trends of groundwater levels, electrical conductivities, and water temperatures and the others showed decreasing trends. However, the non-parametric analyses with monthly median values revealed that $14.8{\sim}20.0%$ of water levels were decreased, $24.2{\sim}36.9%$ of electrical conductivities were increased, and $27.4{\sim}32.5%$ of water temperatures were increased at a confidence level of 99%. Highly proportions of increasing or decreasing trends were unexpected and they resulted from the relatively short term of data collection (maximum 6 years). Meanwhile, the investigation of groundwater around the national groundwater monitoring stations showed that the decreasing or increasing trends of water levels, electrical conductivities, themselves, didn't indicate directly groundwater hazards such as groundwater depletion or groundwater contamination. Both the values and variation rates (slopes) of water level, electrical conductivity and temperature in the longer period are considered simultaneously. This study is the first comprehensive work in analyzing trends of groundwater data obtained from the national groundwater monitoring stations. Based on this study, the periodical and regular analysis of groundwater data is essentially required to grasp the overall variational trend of groundwater resources in the country.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.95-103
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• 1998

Azzalini and Bowman proposed the pseudo-likelihood ratio test for checking the linear relationship using kernel regression estimator when the error of the regression model follows the normal distribution. We modify their method with the bootstrap technique to construct a new test, and examine the power of our test through simulation. Our method can be applied to the case where the distribution of the error is not normal.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.733-745
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• 2017

Local composite quantile regression is a useful non-parametric regression method widely used for its high efficiency. Data smoothing methods using kernel are typically used in the estimation process with performances that rely largely on the smoothing parameter rather than the kernel. However, $L_2$-norm is generally used as criterion to estimate the performance of the regression function. In addition, many studies have been conducted on the selection of smoothing parameters that minimize mean square error (MSE) or mean integrated square error (MISE). In this paper, we explored the optimality of selecting smoothing parameters that determine the performance of non-parametric regression models using local linear composite quantile regression. As evaluation criteria for the choice of smoothing parameter, we used mean absolute error (MAE) and mean integrated absolute error (MIAE), which have not been researched extensively due to mathematical difficulties. We proved the uniqueness of the optimal smoothing parameter based on MAE and MIAE. Furthermore, we compared the optimal smoothing parameter based on the proposed criteria (MAE and MIAE) with existing criteria (MSE and MISE). In this process, the properties of the proposed method were investigated through simulation studies in various situations.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.106-114
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• 1997

The smoothing parameter or bandwidth is crucial to performance of the kernel based regression estimator. So the choice of a "optimal" smoothing parameter produce a single curve estimate. If a single estimate is replaced by a family of estimates, it become easy that we understand what varies with choice of the smoothing parameter. This paper suggests the threshold of the maximum bandwidth and the number of the family members in the regression context.n context.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.27-41
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• 2008

A graphical method of checking the adequacy of a generalized linear model is proposed. The graph helps to assess the assumption that the link function of mean can be expressed as a linear combination of explanatory variables in the generalized linear model. For the graph the boosting technique is applied to estimate nonparametrically the relationship between the link function of the mean and the explanatory variables, though any other nonparametric regression methods can be applied. Through simulation studies with normal and binary data, the effectiveness of the graph is demonstrated. And we list some limitations and technical details of the graph.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.19-33
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• 2008

Linear regression method, proposed by Haseman and Elston(1972), for detecting linkage to a quantitative trait of sib pairs is a linkage testing method for a single locus and a single trait. However, multivariate methods for detecting linkage are needed, when information from each of several traits that are affected by the same major gene are available on each individual. Amos et al. (1990) extended the regression method of Haseman and Elston(1972) to incorporate observations of two or more traits by estimating the principal component linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. But, it is impossible to control the probability of type I errors with this method at present, since the exact distribution of the statistic that they use is yet unknown. In this paper, we propose a multivariate nonparametric trend test for detecting linkage to multiple traits. We compared with a simulation study the efficiencies of multivariate nonparametric trend test with those of the method developed by Amos et al. (1990) for quantitative traits data. For multivariate nonparametric trend test, the results of the simulation study reveal that the Type I error rates are close to the predetermined significance levels, and have in general high powers.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.119-130
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• 2014

This paper is based on water information system of NIE, National Institute of Environmental Research. We used monthly data of water quality from January, 2013 to August, 2013 starting from measuring point A (nbA) to measuring point N (nbN) located along the Nakdong river main stream. Statistical water quality analysis of BOD (biological oxygen demand) is specified by R programming depending on month, year, and points. Based on BOD measured from Nakdong river's measuring points, we used exploratory data analysis and locally weighted scatter plot smoother (Lowess) trend analysis, which is a method of non-parametic regression analysis, to analyze long-term water tendency and water quality distribution depending on points. Also, we analyzed the period and the measuring point of which the outliers are abundant. As a result, compared to BOD measured in nbM located in Busan along the downstream, BOD measured in nbG located in Daegu and nbI located in Changwon along the midstream showed higher rate of water pollution at a severe level.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.33-39
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• 2013

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

• The Korean Journal of Financial Management
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• v.9 no.1
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• pp.83-109
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• 1992

본 연구는 다변량회귀모형(多變量回歸模型)이 동일한 산업내 동일한 시기에 이루어진 규제변동(規制變動)의 재무효과를 측정하는 데에 시장모형(市場模型)보다 장기간에 걸친 복수의 가변적 발표내용, 규제관련기업의 차별적 주가수익반응, 그리고 주가수익잔차간 높은 상관관계 등의 규제특성과 방법론적 문제점을 해결하는 데에 유용한 사건모형(事件模型)임을 실증하고자 한다. 본 연구는 규제변동의 실증적 사례로서 1988년 12월 2일 정부가 발표한 ${\ulcorner}$자본시장국제화의 단계적 확대추진계획${\lrcorner}$에 이르기까지의 일련의 법제적 조치와 발표내용을 사건으로 하여 금융증권산업내 은행, 증권회사, 보험회사 그리고 투자금융회사의 평균적, 개별적, 포트폴리오 비정상수익에 관한 제반공동가설을 모수추정(母數推定)의 제약(制約)에 따라 비제약적(非制約的) 다변량회귀모형(多變量回歸模型) 또는 제약적(制約的) 다변량회귀모형(多變量回歸模型)으로 검증하였다. 모든 13개 발표사건에 대한 평균적, 개별적, 포트폴리오 비정상수익의 가설검증결과에서 은행과 증권회사는 모두 통계적으로 비유의적 반응을 보인 반면, 보험회사와 투자금융회사는 최종발표일이 다가오면서 일부 발표사건에 유의적인 평균반응과 개별반응을 보였다. 특히 모든 금융증권기관은 모든 사건에 비유의적 포트폴리오반응을 보여, Stigler가 제시한 '부(富)의 이전가설(移轉假說)'은 기각되지 못하였다.