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Performance of partial Mann-Kendall tests for trend detection in the presence of covariates
Environmetrics, 2002AbstractTrend 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.
Claudia Libiseller, Anders Grimvall
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Multiple Şen-innovative trend analyses and partial Mann-Kendall test
Journal of Hydrology, 2018Abstract 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
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Exact distribution of the Mann–Kendall trend test statistic for persistent data
Journal of Hydrology, 2009The 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.
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MANN–KENDALL TREND DETECTION FOR PRECIPITATION AND TEMPERATURE IN BANGLADESH
International Journal of Big Data Mining for Global Warming, 2022This study examined both long-term and short-term trends and fluctuations in rainfall and temperature over 34 meteorological stations located at seven regions in Bangladesh. Descriptive statistical analysis and Mann–Kendall trend test were utilized to investigate the variability of the rainfall and temperature of all stations in Bangladesh.
LIPON CHANDRA DAS +2 more
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Rainfall Trend Analysis by Mann–Kendall Test in Syria
The Arab World Geographer, 2022This study investigates monthly, seasonal, and annual rainfall trends using the Mann–Kendall (MK) test, Sen’s slope (SS) method and linear regression analysis in Syria. Historical monthly rainfall records for the period 1960 to 2021 from 17 meteorological stations across the study area were used.
Sattam S. Al Shogoor +2 more
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On the effectiveness of Mann-Kendall test for detection of software aging
2013 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 2013Software aging (i.e. progressive performance degradation of long-running software systems) is difficult to detect due to the long latency until it manifests during program execution. Fast and accurate detection of aging is important for eliminating the underlying defects already during software development and testing.
Fumio Machida +3 more
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Non-monotonic trend analysis using Mann–Kendall with self-quantiles
Theoretical and Applied Climatology, 2023Recently, climate change makes itself felt at increasing levels due to rising temperatures, irregular precipitation patterns and changing weather events. Although the frequently used Mann-Kendall (MK) method has disadvantages such as needing serial independence, it helps to detect monotonic trends to investigate climate change effects on a given time ...
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A modified Mann-Kendall trend test for autocorrelated data
Journal of Hydrology, 1998One 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
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A Contextual Mann‐Kendall Approach for the Assessment of Trend Significance in Image Time Series
Transactions in GIS, 2011AbstractOne of the most common problems in estimating trends in image time series is the presence of contaminants such as clouds. There are many techniques for estimating robust trends but evaluating the significance of the trends can be difficult due to this increased variance. This article presents a novel approach called the Contextual Mann‐Kendall (
Neeti Neeti, J. Ronald Eastman
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