• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.11-19
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• 2009

A number of trend test methods, i.e., Military Handbook test and Laplace test etc., have been applied to investigate recurrent failures trend in repairable systems. Existing methods provide information about only existence of trend in the system. In this paper, we propose a new change-point test based on the Schwarz Information Criterion(SIC). The change-point approach is more informative than other trend test methods in that it provides the number of change-points and the location of change-points if it exists, as well as the existence of change-point for recurrent failures. The change-point test is applied to nine 300MW generating units operated in East China. We confirm that the change-point test has a potential for establishing optimal preventive maintenance policy by detecting change-point of failure rate.

• 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.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.219-227
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• 2013

Time series data including change, jump, trend and periodicity generally have nonstationarity. Especially, various methods have been proposed to identify the trend about hydrological time series data. However, among various methods, evaluation about capability of each trend test has not been done a lot. Even for the same data, each method may show the different result. In this study, the simulation was performed for identification about the changes in trend analysis according to the statistical characteristics and the capability in the trend analysis. For this purpose, power test for the trend analysis is conducted using Men-Kendall test, Hotelling-Pabst test, t test and Sen test according to the slope, sample size, standard deviation and significance level. As a result, t test has higher statistical power than the others, while Mann-Kendall, Hotelling-Pabst, and Sen tests were similar results.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.789-798
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• 2000

The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.235-238
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• 2004

In this paper, we will present the implementation method of telemetry trend analysis in KOMPSAT-2 (KOrea Multi Purpose SATellite II), and then we will show the test result of trend analysis with telemetry data. Trend Analysis function is one of the module of Satellite Operations Subsystem and that analyzes the telemetry data of satellite state of health and telemetry trend for operation support. With this system many clients can analyze telemetry data simultaneously.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.667-681
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• 2013

In this study, monthly and seasonal dissolved oxygen trends of 19 water quality measurement stations in Sapgyo stream watershed were analyzed using monthly dissolved oxygen (DO) data measured for 16 years (1995~2010). Mann-Kendall trend test and Sen's slope estimator were carried out for trend analysis. Furthermore, Sapgyo stream watershed was divided into four different sections (Sapgyo stream, Muhan stream, Gykgyo stream, and Sapgyo lake) and chi-square test of homogeneity for DO trend was carried out for four different sections. The study results indicated that most of water quality measurement stations showed increasing or non-significant trend of DO on a monthly and seasonal basis. The chi-square test of homogeneity for each water quality measurement station showed the statistical homogeneity in seasonal DO trend; however, the test results showed the statistical non-homogeneity in monthly DO trend for the stations located in the reservoir. Overall, the dissolved oxygen trend in each water quality measurement station showed different patterns depending on the location of each station and season.

• Journal of Wetlands Research
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• v.6 no.4
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• pp.35-43
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• 2004

The non-parametric Mann-Kendall(MK) statistical test has been widely used to assess the significance of trend in hydrologic time series. The test requires sample data should be serially independent. If sample data is serially correlated, the presence of serial correlation in a time series will affect the test ability for trend analysis. So, we would like to use the modified MK test which uses the effective sample size(ESS) to eliminate the effect of serial correlation in a series. This study investigates the ability of ESS to eliminate the influence of serial correlation of MK test by Monte Carlo simulation and by real series. As the results, MK test shows the increase of trend rate as the serial correlation is increased but the modified MK test shows ESS can eliminate the serial correlation for trend analysis. Therefore we confirmed the modified MK test is a very useful tool for trend analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.424-424
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• 2017

Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.195-202
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• 2002

The problem of trend change in the mean residual life is great Interest in the reliability and survival analysis. In this paper, a new test statistic for testing whether or not the mean residual life changes its trend Is developed. It is assumed that neither the change point nor the proportion at which the trend change occurs is known. The asymptotic null distribution of test statistic is established and asymptotic critical values of the asymptotic null distribution is obtained. Monte Carlo simulation is used to compare the proposed test with previously known tests.