• 대한교통학회:학술대회논문집
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• 대한교통학회 1999년도 제36회 학술발표회논문집
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• pp.452-457
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• 1999

• 한국물환경학회지
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• 제30권2호
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• pp.148-158
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• 2014

In order to assess the effect of TMDLs management and improve that in the future, it is necessary to analyze long-term changes in water quality during management period. Therefore, long term trend analysis of BOD was performed on thirty monitoring stations in Geum River TMDL unit watersheds. Nonparametric trend analysis method was used for analysis as the water quality data are generally not in normal distribution. The monthly median values of BOD during 2004~2010 were analyzed by Seasonal Mann-Kendall test and LOWESS(LOcally WEighted Scatter plot Smoother). And the effect of Total Maximum Daily Loads(TMDLs) management on water quality changes at each unit watershed was analyzed with the result of trend analysis. The Seasonal Mann-Kendall test results showed that BOD concentrations had the downward trend at 10 unit watersheds, upward trend at 4 unit watersheds and no significant trend at 16 unit watersheds. And the LOWESS analysis showed that BOD concentration began to decrease after mid-2009 at almost all of unit watersheds having no trend in implementation plan watershed. It was estimated that TMDLs improved water quality in Geum River water system and the improvement of water quality was made mainly in implementation plan unit watershed and tributaries.

• Journal of Acupuncture Research
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• 제20권1호
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• pp.144-158
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• 2003

This study was carried out to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research, For study, 551 original articles which used statistical techniques in their data analysis were selected form the articles published in The journal of Korean Acupuncture & Moxibustion Society(JKAMS) between 1984 to 2002. among them, 122 articles used descriptive statistics while 429 articles used inferential statistics for data analysis. For that 429 articles, t-test (189 articles), analysis fo variance (111 articles), chi-square test (14 articles), correlation (10 articles), regression analysis (4 articles), factor analysis(5 articles), or nonparametric test (23 articles) were chose to analyze the data. Nonparametric approach has substantial power in case data do not meet the assumption of normality. This method is not only easy to use ut also provides measures of the statistical variation of nominal and ordinal scale. This study shows that more and more recent papers use nonparametric test compared to the old articles. nine different statistical software or packages (SAS, SPSS, Statview, Minitab, Sigma plot, ISP, Graphpad prism, Excel, Access) have been used in the articles published JKMAS. High level statistical techniques such as SAS, SPSS, and Statview are user friendly and used most for acupuncture and Moxibustion research. Including tables and plots in an article facilitates understanding family process data from a descriptive standpoint, minimized erroneous statistical conclusions, and clarifies theoretically important relationships among variables. Table and plots have been used 500 and 233 articles, respectively. A computer procedure is proposed and illustrated with statistical packages using SAS, SPSS, Statview and ISP.

• Membrane and Water Treatment
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• 제10권5호
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• pp.339-352
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• 2019

Long term water quality change was analyzed to evaluate the effect of the Total Maximum Daily Load (TMDL) policy. A trend analysis was performed for biochemical oxygen demand (BOD) and total phosphorus (TP) concentrations data monitored at the outlets of the total 41 TMDL unit watersheds of the Nakdong River in the Republic of Korea. Because water quality data do not usually follow a normal distribution, a nonparametric statistical trend analysis method was used. The monthly mean values of BOD and TP for the period between 2004 and 2015 were analyzed by the seasonal Mann-Kendall test and the locally weighted scatterplot smoother (LOWESS). The TMDL policy effect on the water quality change of each unit watershed was analyzed together with the results of the trend analysis. From the seasonal Mann-Kendall test results, it was found that for BOD, 7.8 % of the 41 points showed downward trends, 26.8 % and the rest 65.9% showed upward and no trends. For TP, 51.2% showed no trends and the rest 48.8% showed downward trends. From the LOWESS analysis results, TP began to decrease in most of the unit watersheds from mid-2010s when intensive chemical treatment processes were introduced to existing wastewater treatment plants. Overall, for BOD, relatively more points were improved in the main stream compared to the points of the tributaries although overall trends were mostly no trend or upward. For TP, about half of the points were improved and the rest showed no trends.

• Communications for Statistical Applications and Methods
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• 제20권2호
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• pp.115-127
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• 2013

This paper provides an effective stock portfolio screening tool for socially responsible investment (SRI) based upon corporate social responsibility (CSR) and financial performance. The proposed approach utilizes nonparametric frontier models. Data envelopment analysis (DEA) has been used to build SRI portfolios in a few previous works; however, we show that free disposal hull (FDH), a similar model that does not assume the convexity of the technology, yields superior results when applied to a stock universe of 253 Korean companies. Over a four-year time span (from 2006 to 2009) the portfolios selected by the proposed method consistently outperform those selected by DEA as well as the benchmark.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.885-898
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• 2012

In this paper, we consider Bayesian approaches to partially linear models, in which a regression function is represented by a semiparametric additive form of a parametric linear regression function and a nonparametric regression function. We make a comparative study on the performance of widely used Bayesian partially linear models in terms of empirical analysis. Specifically, we deal with three Bayesian methods to estimate the nonparametric regression function, one method using Fourier series representation, the other method based on Gaussian process regression approach, and the third method based on the smoothness of the function and differencing. We compare the numerical performance of three methods by the root mean squared error(RMSE). For empirical analysis, we consider synthetic data with simulation studies and real data application by fitting each of them with three Bayesian methods and comparing the RMSEs.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.11-19
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• 2015

기업에서는 매달 제품이 일정 수량만큼 수송되어 판매되고, 이들 중 일부는 반환 또는 클레임이 제기된다. 이전의 연구에서는 품질보증 반환 데이터의 반환율을 그래프상에 어떻게 타점할 것인지 먼저 살펴보았고, 이어서 이런 데이터를 좌측 및 우측 중도중단 데이터의 결합으로 생각하여 와이블 분포등을 적합시켜 신뢰성분석을 실시해보았다. 본 연구에서는 우선 수송된 제품이 곧 판매된 것으로 보고, 이들 제품의 품질보증 반환 데이터에 대해 비모수적인 방법을 적용하여 시간에 따른 신뢰도의 추이를 살펴보고 모수적 방법에 의한 결과와 비교해본다. 한편, 제품이 생산되어 판매지로 수송된 경우 소비자의 손에 들어가기까지에는 시차가 있기 마련인데, 이와 같이 수송된 제품이 시차를 두고 판매되는 경우 이런 제품의 품질보증 반환 데이터에 대해서는 어떻게 분석을 실시해야 하는지 살펴본다.

• 한국전산구조공학회논문집
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• 제30권1호
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• pp.87-94
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• 2017

신뢰성 해석 및 신뢰성기반 최적설계는 불확실성을 고려한 확률변수를 입력 값으로 요구하며, 확률변수는 모수적 비모수적 통계모델링 방법을 사용하여 확률분포함수의 형태로 정량화 된다. 신뢰성 해석과 같은 통계적 해석은 입력되는 확률분포함수의 특성이 결과값에 영향을 미치게 되며, 확률분포함수는 통계모델링 방법에 따라 다른 형태를 가지게 된다. 본 연구에서는 모수적 통계모델링 방법인 순차적 통계모델링 방법과 비모수적 방법인 커널밀도추정을 사용하여 데이터의 개수에 따른 통계모델링의 결과를 분석하였다. 또한 수치예제를 통해 두 가지 기법에 따른 신뢰성 해석의 결과를 분석하였고, 데이터의 개수에 따른 적절한 기법을 제안하였다.

• 약학회지
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• 제43권2호
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• pp.160-168
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• 1999

The purpose of this study was to determine pharmacokinetic parameters of vancomycin using peak and trough plasma level (PTL) and Bayesian analysis in 20 Korean normal volunteers, 16 gastric cancer and 12 lymphoma patients and also using the compartment model dependent (nonlinear least squares regression: NLSR) and compartment model independent (Lagrange) analysis in 10 ovarian cancer patients. Nonparametric expected maximum (NPEM) algorithm for calculation of the population pharmacokinetic parameters was used, and these parameters were applied for clinical pharmacokinetic parameters by Bayesian analysis. Vancomycin was administered as dose of 1.0 g every 12 hrs for 3 days by IV infusion over 60 minutes in normal volunteers, gastric cancer and lymphoma patients. Population pharmacokinetic parameters, K and Vd in gastric cancer and lymphoma patients using NPEM algorithm were $0.158{\pm}0.014{\;}hr^{-1},{\;}0.630{\pm}0.043{\;}L/kg{\;}and{\;}0.131{\pm}0.0261{\;}hr^{-1},{\;}0.631{\pm}0.089{\;}L/kg$ respectively. The K and Vd in gastric cancer and lymphoma patients using Bayesian analysis were $0.151{\pm}0.027,{\;}0.126{\pm}0.056{\;}hr^{-1}{\;}and{\;}0.62{\pm}0.105,{\;}0.63{\pm}0.095{\;}L/kg$. The K and Vd in ovarian cancer patient using the NLSR and Lagrange analysis were $0.109{\pm}0.008,{\;}0.126{\pm}0.012{\;}hr^{-1}{\;}and{\;} 0.76{\pm}0.08,{\;}0.69{\pm}0.19{\;}L/kg$, respectively. It is necessary for effective dosage regimen of vancomycin in cancer patients to use these population parameters.

• 약학회지
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• 제40권1호
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• pp.1-9
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• 1996

The purpose of this investigation was to determine pharmacokinetic parameters of gentamicin using nonlinear least square regression(NLSR) and Bayesian analysis in Korean normal volunteers and gastrointestinal surgical patients. Nonparametric expected maximum(NPEM) method for population pharmacokinetic parameters was used. Gentamicin was administered every 8 hours for 3 days by infusion over 30 minutes. The volume of distribution(V) and elimination rate constant(K) of gentamicin were $0.226{\pm}0.032,\;0.231{\pm}0.063L/Kg\;and\;0.357{\pm}0.024,\;0.337{\pm}0.041hr^{-1}$ for normal volunteers and gastrointestinal surgical patients using NLSR analysis. Population pharmacokinetic parameters, KS and VS were $0.00344{\pm}0.00049(hr{\cdot}ml/min/1.73m^2)^{-1}\;and\;0.214{\pm}0.0502L/Kg$ for gastrointestinal surgical patients using NPEM method. The V and K were $0.216{\pm}0.048L/Kg\;and\;0.336{\pm}0.043hr^{-1}$ for gastrointestinal surgical patients using Bayesian analysis. There were no differences in gentamicin pharmacokinetics between NLSR and Bayesian analysis in gastrointestinal surgical patient.