SSP {DFA}

Self-similarity parameter (SSP)

Description

This function estimates the self-similarity parameter (SSP), also known as scaling exponent or alpha.

Usage

SSP(file,scale = 2^(1/8),box_size = 4,m=1)

Arguments

file

Univariate time series (must be a vector or data frame)

scale

Specifies the ratio between successive box sizes (by default scale = 2^(1/8))

box_size

Vector of box sizes (must be used in conjunction with scale = "F")

m

An integer of the polynomial order for the detrending (by default m=1)

Details

The DFA fluctuation can be computed in a geometric scale or for different choices of boxes sizes.

Value

Estimated alpha is a real number between zero and two.

Note

It is not possible estimating alpha for multiple time series at once.

Author(s)

Ian Meneghel Danilevicz and Victor Barreto Mesquita

References

C.-K. Peng, S.V. Buldyrev, S. Havlin, M. Simons, H.E. Stanley, A.L. Goldberger Phys. Rev. E, 49 (1994), p. 1685

Mesquita, V., Filho, F., Rodrigues, P. (2020). Detection of crossover points in detrended fluctuation analysis: An application to EEG signals of patients with epilepsy. Bioinformatics. 10.1093/bioinformatics/btaa955.

Examples

# Estimate self-similarity of a very known time series available on R base: the sunspot.year.
# Then the spend time with each method is compared.
library(DFA)
SSP(sunspot.year, scale = 2)
SSP(sunspot.year, scale = 1.2)

time1 = system.time(SSP(sunspot.year, scale = 1.2))
time2 = system.time(SSP(sunspot.year, scale = 2))

time1
time2