prewhite: Compute the prewhitened datasets

In mannkendall/R: MannKendall trends for geophysical time series

Description

calculate all the necessary prewhitened datasets to asses the statistical significance and to compute the Sen's slope for each of the prewhitening method, including 3PW

Usage

prewhite(data.ts, column, resolution, alpha.ak = 95)

Arguments

data.ts	it is a dataframe with a column named "Time" as POSIXct with timezone UTC and the other columns with observations
column	the number column of the data to be analyzed (must be greater than 2)
resolution	the measurement resolution, i.e. delta value below which 2 measurements are considered equivalent. It is used to compute the number of ties
alpha.ak	statistical significance in percentage for the first lag autocorrelation (default is 95)

Value

data.PW a dataframe with 6 columns: Time (as POSIXct in UTC) = time of the series PW = PW with the first lag autocorrelation of the data PW.cor = PW corrected with 1/(1-ak1) TFPW.WS = PW with the first lag autocorrelation of the data after detrending computed from PW data (see Wang & Swail) TFPW.Y = method of Yue et al 2002, not 1/1-ak1) correction detrend on original data VCTFPW = PW with the first lag autocorrelation of the data after detrending + correction of the PW data for the variance (see Wang 2015)

Author(s)

Martine Collaud Coen ([e-mail]), MeteoSwiss (CH) and Alessandro Bigi ([e-mail]), University of Modena and Reggio Emilia (IT)

References

Collaud Coen, M., Andrews, E., Bigi, A., Romanens, G., Martucci, G., and Vuilleumier, L.: Effects of the prewhitening method, the time granularity and the time segmentation on the Mann-Kendall trend detection and the associated Sen's slope, Atmos. Meas. Tech., https://doi.org/10.5194/amt-2020-178, 2020.

mannkendall/R documentation built on Feb. 2, 2022, 7:31 p.m.