# MFDFA: MultiFractal Detrended Fluctuation Analysis In RespirAnalyzer: Analysis Functions of Respiratory Data

## Description

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

## Usage

 `1` ```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.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```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 March 1, 2021, 5:06 p.m.