ts_sumorder: Adjust time series by summation order

In FredHasselman/casnet: A Toolbox for Studying Complex Adaptive Systems and Networks

Adjust time series by summation order

Description

Many fluctuation analyses assume a time series' Hurst exponent is within the range of 0.2 - 1.2. If this is not the case it is sensible to make adjustments to the time series, as well as the resutling Hurst exponent.

Usage

ts_sumorder(y, scaleS = NULL, polyOrder = 1, dataMin = 4)

Arguments

y	A time series of numeric vector
scaleS	The scales to consider for DFA1
polyOrder	Order of polynomial for detrending in DFA (default = 1)
dataMin	Minimum number of data points in a bin needed to calculate detrended fluctuation

Details

Following recommendations by https://www.frontiersin.org/files/Articles/23948/fphys-03-00141-r2/image_m/fphys-03-00141-t001.jpgIhlen (2012), a global Hurst exponent is estimated using DFA and y is adjusted accordingly:

• ⁠1.2 < H < 1.8⁠ first derivative of y, atribute Hadj = 1

• H > 1.8 second derivative of y, atribute Hadj = 2

• H < 0.2 y is centered and integrated, atribute Hadj = -1

• ⁠0.2 <= H <= 1.2 ⁠ y is unaltered, atribute Hadj = 0

Value

The input vector, possibly adjusted based on H with an attribute "Hadj" containing an integer by which a Hurst exponent calculated from the series should be adjusted.

References

Ihlen, E. A. F. E. (2012). Introduction to multifractal detrended fluctuation analysis in Matlab. Frontiers in physiology, 3, 141.

See Also

Other Time series operations: ts_center(), ts_changeindex(), ts_checkfix(), ts_detrend(), ts_diff(), ts_discrete(), ts_duration(), ts_embed(), ts_integrate(), ts_levels(), ts_peaks(), ts_permtest_block(), ts_permtest_transmat(), ts_rasterize(), ts_sd(), ts_slice(), ts_slopes(), ts_standardise(), ts_symbolic(), ts_trimfill(), ts_windower()

FredHasselman/casnet documentation built on May 5, 2024, 9:38 p.m.