MFDFA: MultiFractal Detrended Fluctuation Analysis

In RespirAnalyzer: Analysis Functions of Respiratory Data

MultiFractal Detrended Fluctuation Analysis

Description

Applies the MultiFractal Detrended Fluctuation Analysis (MFDFA) to time series.

Usage

MFDFA(tsx, scale, m, q)

Arguments

tsx	Univariate time series (must be a vector).
scale	Vector of scales.
m	An integer of the polynomial order for the detrending.
q	q-order of the moment.

Value

A list of the following elements:

• Hq q-order Hurst exponent.

• tau_q Mass exponent.

• hq Holder exponent.

• Dq singularity dimension.

• Fqi q-order fluctuation function.

• line linear fitting line of fluctuation function.

References

Zhang T, Dong X, Chen C, Wang D, Zhang XD. RespirAnalyzer: an R package for continuous monitoring of respiratory signals.

Examples

data("TestData") # load Data from TestData dataset
Fs <- 50
Peaks <- find.peaks(Data[,2],Fs,lowpass=TRUE,freq=1,MovingAv=FALSE,
                    W=FALSE,filter=TRUE,threshold=0.05)
head(Peaks)
PP_interval <- diff(Peaks$PeakIndex)/Fs
## Computing Multifractal
exponents=seq(3, 9, by=1/4)
scale=2^exponents
q=-10:10
m=2
Result <- MFDFA(PP_interval, scale, m, q)
Coeff <- fit.model(Result$Hq,q)
print(Coeff)
Para<- -log(Coeff)/log(2)
Para[3]=Para[1]-Para[2]
names(Para)<-c("Hmax","Hmin","DeltaH")
Para

PP_Hq <- Result$Hq
PP_hq <- Result$hq
PP_Dq <- Result$Dq
PP_Para <-Para

RespirAnalyzer documentation built on July 9, 2023, 7 p.m.