• Title/Summary/Keyword: Nonparametric trend analysis

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

  • Lee, Sang-Hoon
    • Journal of Environmental Impact Assessment
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    • v.4 no.2
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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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A Study on the Water Quality Changes of TMDL Unit Watershed in Guem River Basin Using a Nonparametric Trend Analysis (비모수 경향분석법 적용을 통한 금강수계 총량관리 단위유역의 수질변화 연구)

  • Kim, Eunjung;Kim, Yongseok;Rhew, Doughee;Ryu, Jichul;Park, Baekyung
    • Journal of Korean Society on Water Environment
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    • v.30 no.2
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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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    • v.16 no.2
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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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    • v.10 no.5
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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.

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

  • Park, Jinsoo;Kim, Yun Bae;Song, Kiburm
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.2
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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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    • v.19 no.4
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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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    • v.26 no.1
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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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A Study of the Urbanization Effect on the Precipitation Pattern in Urban Areas (도시화가 도시지역 강수변화에 미치는 영향 연구)

  • Oh, Tae-Suk;Ahn, Jae-Hyun;Moon, Young-Il;Kim, Jong-Suk
    • Journal of Korea Water Resources Association
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    • v.38 no.10 s.159
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    • pp.885-894
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    • 2005
  • Since the 1970s, rapid Industrialization has brought urbanization nationwide. In this paper, thirty one years data(1973-2003) ate used to evaluate variability of major cities. Before assessing the context between urbanization and variability of rainfall, the rural areas are selected to compare with urban ones. Thus, average, trends, variations, and nonparametric frequency analysis methods were employed for evaluating variation of annual precipitation, seasonal precipitation, 1 hour annual maximum design rainfall and 24 hour annual maximum design rainfall for both urban and rural areas. The result have shown that summer precipitation relatively increased In urban areas compared to that in rural areas.

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

  • Choi, Hyun-Mi;Lee, Jin-Yong
    • Journal of Soil and Groundwater Environment
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    • v.14 no.5
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    • pp.41-50
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    • 2009
  • Water levels in groundwater monitoring wells of Jeju Island were analyzed using parametric and non-parametric trend analyses. Number of used monitoring wells in the analysis are 94 among totally 106 monitoring wells and the monitoring period is greater than single year, from 2001 to 2009. For the trend analysis, both parametric (linear regression) and nonparametric (Mann-Kendall trend test and Sen's trend test) methods were adopted. Results of the linear regression analysis on daily basis indicated that about 58.5% of the monitoring wells showed a decreasing trend, and analysis using monthly median indicated that about 79.8% showed a decreasing trend. The Mann-Kendall trend test and Sen's trend test with monthly median values in confidence levels of 95% and 99% showed the same analysis results. In confidence level of 95%, 32% were decreased, 3% were increased and the remains showed no trend. However, in confidence level of 99%, 16% were decreased, 2% were increased and the remains showed no trend. The largest decline rates of water levels were detected mainly at the coast of the northwestern and southwestern parts, which is expected to closely related to the increased pumping in the urban area and tourist resort.

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

  • Cho, Cha-Hyun;Yum, Bong-Jin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.5
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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.