SSP {GGIR} | R Documentation |
Estimated self-similarity parameter
Description
This function estimates the self-similarity parameter (SSP), also known as scaling exponent or alpha.
Usage
SSP(data,scale = 2^(1/8),box_size = 4,m=1)
Arguments
data |
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 <ian.meneghel-danilevicz@inserm.fr> Victor Barreto Mesquita <victormesquita40@hotmail.com>
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, Victor & Filho, Florencio & Rodrigues, Paulo. (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.
## Not run:
ssp = SSP(sunspot.year)
## End(Not run)