• 제목/요약/키워드: Nonparametric trend analysis

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수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 환경영향평가
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    • 제4권2호
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    • pp.93-103
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    • 1995
  • This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

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비모수 경향분석법 적용을 통한 금강수계 총량관리 단위유역의 수질변화 연구 (A Study on the Water Quality Changes of TMDL Unit Watershed in Guem River Basin Using a Nonparametric Trend Analysis)

  • 김은정;김용석;류덕희;류지철;박배경
    • 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.

Statistical Bias and Inflated Variance in the Genehunter Nonparametric Linkage Test Statistic

  • Song, Hae-Hiang;Choi, Eun-Kyeong
    • Communications for Statistical Applications and Methods
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    • 제16권2호
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    • pp.373-381
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    • 2009
  • Evidence of linkage is expressed as a decreasing trend of the squared trait difference of two siblings with increasing identical by descent scores. In contrast to successes in the application of a parametric approach of Haseman-Elston regression, notably low powers are demonstrated in the nonparametric linkage analysis methods for complex traits and diseases with sib-pairs data. We report that the Genehunter nonparametric linkage statistic is biased and furthermore the variance formula that they used is an inflated one, and this is one reason for a low performance. Thus, we propose bias-corrected nonparametric linkage statistics. Simulation studies comparing our proposed nonparametric test statistics versus the existing test statistics suggest that the bias-corrected new nonparametric test statistics are more powerful and attains efficiencies close to that of Haseman-Elston regression.

Evaluation of long-term water quality management policy effect using nonparametric statistical methods

  • Jung, Kang Young;Ahn, Jung Min;Cho, Sohyun;Lee, Yeong Jae;Han, Kun Yeun;Shin, Dongseok;Kim, Kyunghyun
    • 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.

추세 시계열 자료의 부트스트랩 적용 (Applying Bootstrap to Time Series Data Having Trend)

  • 박진수;김윤배;송기범
    • 한국경영과학회지
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    • 제38권2호
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    • pp.65-73
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    • 2013
  • In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

Trend Analysis of Stream Qualities In Nakdong River by the LOWESS method

  • Yoon, Yong-Hwa;Um, Hee-Jung;Kim, Jong-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1019-1026
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    • 2008
  • The goal of this paper is to analysis the trend of stream quality about the upstream, middle stream and high areas of Nakdong River measurement points from January 1998 to December 2006. and to suggest some policy alternatives in Nakdong river. It used the three different monthly time series data such as BOD (biochemical oxygen demand), TN (Total Nitrogen) and TP(Total Phosphorus), of the three of Nakdong River measurement points. BOD, TN and TP data are analyzed with the LOWESS(Locally Weighted Scatter plot Smoother) nonparametric method.

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Nonparametric Tests for Monotonicity Properties of Mean Residual Life Function

  • Jeon, Jong-Woo;Park, Dong-Ho
    • Journal of the Korean Statistical Society
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    • 제26권1호
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    • pp.101-116
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    • 1997
  • This is primarily an expository paper that presents several nonparametric procedures for testing exponentiality against certain monotonicity properties of the mean residual life function, tests against the trend change in such function attract a great deal of attention of late in reliability analysis. In this note, we present some of the known testing procedures regarding the behavior of mean residual life function. These tests are also compared in terms of asymptotic relative efficiency and empirical power against a few alternatives. The tests based on incomplete data are also briefly discussed.

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도시화가 도시지역 강수변화에 미치는 영향 연구 (A Study of the Urbanization Effect on the Precipitation Pattern in Urban Areas)

  • 오태석;안재현;문영일;김종석
    • 한국수자원학회논문집
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    • 제38권10호
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    • pp.885-894
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    • 2005
  • 1970년대 이후, 우리나라는 산업화에 따른 급격한 도시화가 이루어졌다. 본 논문에서는 우리나라의 대표적인 도시인 서울특별시 및 6대 광역시의 1973년부터 2003년까지의 31개년의 강수랑 자료를 이용하여 강수량의 변화에 대하여 분석하였다. 이와 함께 도시화에 따른 강수량의 변동성을 평가하기 위해서 비도시 지역을 선정하였으며 도시 지역의 강수량 변화와 비교하였다. 도시 지역과 비도시 지역의 연강수량, 계절별 강수량, 지속 시간 1시간 및 24시간연최대 강수량에 대해 임의기간에 따른 평균 분석, 경향성 분석, 변동성 분석, 비매개변수적 빈도 해석을 수행한 결과, 도시화 지역에서 비도시화 지역보다 강우 증가율이 더 컸으며, 특히 여름 강수량의 증가량이 두드러졌다.

제주도 지하수 관측망 수위에 대한 모수 및 비모수 변동경향 분석 (Parametric and Non-parametric Trend Analyses for Water Levels of Groundwater Monitoring Wells in Jeju Island)

  • 최현미;이진용
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제14권5호
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    • pp.41-50
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    • 2009
  • 제주도 지하수관측망의 지하수위 측정 자료에 대하여 모수 및 비모수 경향분석을 수행하였다. 분석대상은 2001년부터 1년 이상 관측된 관측정으로 총 106개 관측정 중 94개가 이에 해당된다. 모수분석은 일평균 및 월중앙값을 이용한 선형회귀분석을 실시하였으며 비모수분석은 월중앙값에 대해 Mann-Kendall trend test와 Sen's trend test를 적용하였다. 선형회귀분석 결과 일평균값에 대하여 58.5%가 감소경향을 나타났으며 월중앙간에 대해서는 79.8%가 감소하는 경향을 보였다. Mann-Kendall trend test와 Sen's trend test를 신뢰수준 95%와 99%로 실시한 결과 두 분석 모두 일치하는 결과를 보였다. 95% 신뢰수준에서는 32%가 감소경향을 보였으며 3%가 증가경향을 나타냈고, 나머지 65%는 경향성이 나타나지 않았다. 또 99%신뢰수준에서는 16%가 감소경향을 보였으며 2%가 증가경향을 나타냈고 그리고 나머지 82%에서는 경향성이 없는 것으로 나타났다. 수위하강이 우세하게 나타난 지역은 제주도 북서부 및 남서부의 해안지역으로 도시 및 관광지에서의 다량의 지하수 양수와 관련 있는 것으로 사료된다.

구간 고장 데이터가 주어진 수리가능 시스템의 신뢰도 분석절차 개발 및 사례연구 (Development of Reliability Analysis Procedures for Repairable Systems with Interval Failure Time Data and a Related Case Study)

  • 조차현;염봉진
    • 한국군사과학기술학회지
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    • 제14권5호
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    • pp.859-870
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    • 2011
  • The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.