Keywords
Hurst; Potential evapotranspiration; Parametric model; R software; Trend analysis
Abstract
We present an R function for testing the trend significance of time series. The function calculates the trend significance using a modified Mann- Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. The function is tested in 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric approach. A significant downward trend was detected in two stations. The R software is now suitable for extensive use in the several fields of the scientific community, allowing a physical consistent of a trend analysis.
BYU ScholarsArchive Citation
Tegos, Aristoteles; Tyralis, Hristos; Koutsoyiannis, Demetris; and Hamed, Khaled
(2017)
"An R function for the estimation of trend significance under the scaling hypothesis- application in PET parametric annual time series,"
Open Water Journal: Vol. 4:
Iss.
1, Article 6.
Available at:
https://scholarsarchive.byu.edu/openwater/vol4/iss1/6
Supplementary file for the R script
