2018
DOI: 10.1007/s00703-018-0592-7
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Non-parametric characterization of long-term rainfall time series

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Cited by 20 publications
(4 citation statements)
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“…Given the limited sample size ( n = 10) in this study, Mann–Kendall (MK) tests are used to examine the temporal changes of the waste diversion rates from 1998 to 2016. MK test is a non-parametric statistical tool that is used to identify monotonic trends in time-series data (Chowdhury et al 2017 ; Tiwari and Pandey 2019 ) and is adopted in the current study to analyze the recycling behavior of different WMSs. Unlike linear regression, the MK test can handle irregular data intervals regardless of data normality distribution (Fu and Weng 2015 ; Wang et al 2016a ), and a normal distribution of the data is not necessary.…”
Section: Methodsmentioning
confidence: 99%
“…Given the limited sample size ( n = 10) in this study, Mann–Kendall (MK) tests are used to examine the temporal changes of the waste diversion rates from 1998 to 2016. MK test is a non-parametric statistical tool that is used to identify monotonic trends in time-series data (Chowdhury et al 2017 ; Tiwari and Pandey 2019 ) and is adopted in the current study to analyze the recycling behavior of different WMSs. Unlike linear regression, the MK test can handle irregular data intervals regardless of data normality distribution (Fu and Weng 2015 ; Wang et al 2016a ), and a normal distribution of the data is not necessary.…”
Section: Methodsmentioning
confidence: 99%
“…One advantage of the Mann-Kendall is that as a non-parametric test, it does not require the series to be normally distributed or linear. The Mann-Kendall test has been proven for its suitability to detect increasing and decreasing trends in climate and environmental data (Alemu & Dioha, 2020) and dependable test for identifying trends in time series rainfall data sets (Bari et al, 2016;Bora et al, 2022;Sharma and Saha, 2017;Tiwari and Pandey, 2018).…”
Section: Methods For Assessing Rainfall Trends and Variabilitymentioning
confidence: 99%
“…The parametric tests such as linear regression and Prais-Winsten regression are the elementary statistical techniques. However, the non-parametric tests are widely accepted for trend analysis because of having several advantages over the parametric tests (Kumar et al 2019;Tiwari and Pandey 2019). Unlike parametric tests, they have lesser assumptions.…”
Section: Introductionmentioning
confidence: 99%