secant: secant method for detection of crossover points

In DFA: Detrended Fluctuation Analysis

secant method for detection of crossover points

Description

Applies the secant method for detection of crossover points on the log-log curve.

Usage

secant(x,y,npoint,size_fit)

Arguments

x	Vector of the decimal logarithm of the boxes sizes.
y	Vector of the decimal logarithm of the DFA calculated in each boxe.
npoint	Number of crossover points calculated on the log-log curve.
size_fit	Number of points of the two semi-curved fitted in the extremes of the log-log curve.

Value

position

Position of the crossover point identified by the secant method.

Author(s)

Victor Barreto Mesquita

Examples

# Example with the data referring to the log fluctuation
#channel curve data calculated for an epileptic subject
#extracted in the Physionet platform.

library(DFA)
data("EEGsignal")
x<-EEGsignal$`log10(boxes)`
y<-EEGsignal$`log10(DFA)`
plot(x,y,xlab="log10(boxes)",ylab="log10(DFA)")

secant(x,y,npoint=2,size_fit=8)

# Example with crossover point fixed in position=20.

library(DFA)
part1 <- seq(1,20)
part2 <- seq(20,1)
y = c(part1,part2)
x<-seq(1,40)
plot(x,y)
secant(x,y,npoint=1,size_fit=8)

DFA documentation built on June 22, 2024, 11:22 a.m.