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Applies the log-amplitude Detrended Fluctuation Analysis (DFA) to nonstationary time series.
DeltaDFA(file,file2,scale = 2^(1/8),box_size = 4,m=1)
Size
log-amplitude Detrended Fluctuation function defined as the difference between the DFA decimal logarithmic of the first time series (file
) and the DFA decimal logarithmic of the second time series (file2
)
Univariate time series (must be a vector or data frame)
Univariate time series (must be a vector or data frame)
Specifies the ratio between successive box sizes (by default scale = 2^(1/8)
)
Vector of box sizes (must be used in conjunction with scale = "F"
)
An integer of the polynomial order for the detrending (by default m=1
).
Victor Barreto Mesquita
The DFA log-amplitude fluctuation can be computed in a geometric scale or for different choices of boxes sizes.
G. F. Zebende, F. M. Oliveira Filho, J. A. L. Cruz, Auto-correlationin the motor/imaginary human eeg signals: A vision about the fdfafluctuations, PloS one 12 (9) (2017).
F. Oliveira Filho, J. L. Cruz, G. Zebende, Analysis of the eeg bio-signalsduring the reading task by dfa method, Physica A: Statistical Mechanicsand its Applications 525 (2019) 664-671.
S. R. Hirekhan, R. R. Manthalkar, The detrended fluctuation and cross-correlation analysis of eeg signals, International Journal of IntelligentSystems Design and Computing 2 (2) (2018) .
#The following examples using the database of financial time series
#collected during the United States bear market of 2007-2009.
# \donttest{
library(DFA)
data("NYA2008")
data("IXIC2008")
file = NYA2008
file2= IXIC2008
DeltaDFA(file,file2,scale = 2^(1/8),box_size = c(4,8,16),m=1)
# }
# \donttest{
# Example with different polynomial fit order.
library(DFA)
data("NYA2008")
data("LSE.L2008")
file = NYA2008
file2= LSE.L2008
DeltaDFA(file,file2,scale = 2^(1/8),box_size = c(4,8,16),m=2)
# }
# \donttest{
# Example using differente choice of overlapping boxes sizes.
library(DFA)
data("NYA2008")
data("IXIC2008")
file = NYA2008
file2= IXIC2008
DeltaDFA(file,file2,scale = "F",box_size = c(4,8,16),m=1)
# }
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