lrcorrelation {DFA} R Documentation

## data frame with log fluctuation channel curve simulated following an ARFIMA process

### Description

The data contains the data frame with log fluctuation channel curve simulated following an ARFIMA process with different DFA exponents ranging from short 0.1 to long 0.9 .

### Usage

data("lrcorrelation")

### Format

A data frame with 40 observations on the following 10 variables.

log10(boxes)

a numeric vector referring to the decimal logarithm of the boxes sizes.

log10(DFA(alpha = 0.1))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.1 and calculated in each boxe.

log10(DFA(alpha = 0.2))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.2 and calculated in each boxe.

log10(DFA(alpha = 0.3))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.3 and calculated in each boxe.

log10(DFA(alpha = 0.4))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.4 and calculated in each boxe.

log10(DFA(alpha = 0.5))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.5 and calculated in each boxe.

log10(DFA(alpha = 0.6))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.6 and calculated in each boxe.

log10(DFA(alpha = 0.7))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.7 and calculated in each boxe.

log10(DFA(alpha = 0.8))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.8 and calculated in each boxe.

log10(DFA(alpha = 0.9))

a numeric vector referring to the decimal logarithm of the Detrended Fluctuation Analysis (DFA) with DFA exponent equal 0.9 and calculated in each boxe.

### Examples

library(DFA)
#library(latex2exp) # it is necessary for legend of the plot function
data(lrcorrelation)
plot(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.9))
,xlab="log10(n)",ylab="log10FDFA(n)",col="black"
,pch=19, ylim= c(-0.8,1.2))
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.8)),type="p"
,col="blue", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.7)),type="p"
,col="red", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.6)),type="p"
,col="green", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.5)),type="p"
,col="brown", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.4)),type="p"
,col="yellow", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.3)),type="p"
,col="orange", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.2)),type="p"
,col="pink", pch=19)
lines(lrcorrelation$log10(boxes),lrcorrelation$log10(DFA(alpha = 0.1)),type="p"
,col="magenta", pch=19)

#legend("bottom", legend=c(TeX("$\alpha_{DFA} = 0.9$"),TeX("$\alpha_{DFA} = 0.8$")
#                          ,TeX("$\alpha_{DFA} = 0.7$"),TeX("$\alpha_{DFA} = 0.6$")
#                          ,TeX("$\alpha_{DFA} = 0.5$"),TeX("$\alpha_{DFA} = 0.4$")
#                          ,TeX("$\alpha_{DFA} = 0.3$"),TeX("$\alpha_{DFA} = 0.2$")
#                          ,TeX("$\alpha_{DFA} = 0.1$"))
#       , col=c("black","blue","red","green","brown","yellow","orange","pink","magenta")
#       , pch=c(19,19,19,19,19,19,19,19,19)
#       , cex = 0.55
#       , ncol = 5
#)



[Package DFA version 0.9.0 Index]