pyMannKendall: a python package for non parametric Mann Kendall family of trend tests

By M. Hussain, Ishtiak Mahmud. Journal of Open Source Software, 2019

623 citations recorded by the source corpus.

Trend analysis is one of the most important measurements in studying time series data. Both parametric and non-parametric tests are commonly used in trend analysis. Parametric tests require data to be independent and normally distributed. On the other hand, non-parametric trend tests require only that the data be independent and can tolerate outliers in the data (Hamed & Rao, 1998). However, parametric tests are more powerful than nonparametric ones.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/be57990a9cf3db9c212f4ee83349ec51960af145

Citations in the corpus

• Large Hail Incidence and Its Economic and Societal Impacts across Europe (2019, neutral): “This discrepancy has already been addressed by Antonescu et al. (2016) and can be noted when comparing the climatologies of tornadoes and large hail over Turkey (Kahraman and Markowski 2014; Kahraman et al. 2016).”