easyclimate.core.mk_test#
Mann-Kendall Test
The Mann-Kendall Trend Test (sometimes called the MK test) is used to analyze time series data for consistently increasing or decreasing trends (monotonic trends). It is a non-parametric test, which means it works for all distributions (i.e. data doesn’t have to meet the assumption of normality), but data should have no serial correlation. If the data has a serial correlation, it could affect in significant level (p-value). It could lead to misinterpretation. To overcome this problem, researchers proposed several modified Mann-Kendall tests (Hamed and Rao Modified MK Test, Yue and Wang Modified MK Test, Modified MK test using Pre-Whitening method, etc.). Seasonal Mann-Kendall test also developed to remove the effect of seasonality.
See also
Hussain et al., (2019). pyMannKendall: a python package for non parametric Mann Kendall family of trend tests.. Journal of Open Source Software, 4(39), 1556, https://doi.org/10.21105/joss.01556