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Multiple Şen-innovative trend analyses and partial Mann-Kendall test

Journal of Hydrology, 2018
Abstract The climate change is an important event that affects hydrological, agricultural and water resources planning variables, and therefore, the hydrologists and meteorologists frequently try to identify trend possibilities especially in rainfall, runoff and temperature time series.
Yavuz Selim Güçlü
exaly   +3 more sources

A modified Mann-Kendall trend test for autocorrelated data

Journal of Hydrology, 1998
One of the commonly used tools for detecting changes in climatic and hydrologic time series is trend analysis. A number of statistical tests exist to assess the significance of trends in time series. One of the commonly used non-parametric trend tests is the Mann-Kendall trend test.
Khaled H. Hamed, A. Ramachandra Rao
openaire   +2 more sources

Exact distribution of the Mann–Kendall trend test statistic for persistent data

Journal of Hydrology, 2009
The distribution-free Mann-Kendall test is widely used for the assessment of significance of trends in many hydrologic and climatic time series. Previous studies have suggested both exact and approximate formulas for the calculation of the variance of the test statistic when the data are serially correlated.
Khaled H Hamed
exaly   +2 more sources

Block bootstrap for Mann–Kendall trend test of serially dependent data

Hydrological Processes, 2012
AbstractMann–Kendall (MK) test for trend detection must be modified when the data are serially correlated, to prevent the detection of false trends. Various approaches are developed for this purpose, such as prewhitening, trend‐free prewhitening, variance correction and block bootstrap. Each method has its own Type I and Type II errors.
Bihrat Onoz, Mehmetçik Bayazit
exaly   +2 more sources

Performance of partial Mann-Kendall tests for trend detection in the presence of covariates

Environmetrics, 2002
AbstractTrend analyses of time series of environmental data are often carried out to assess the human impact on the environment under the influence of natural fluctuations in temperature, precipitation, and other factors that may affect the studied response variable. We examine the performance of partial Mann–Kendall (PMK) tests, i.e.
Anders Grimvall
exaly   +2 more sources

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