lrcorrelation {DFA} | R Documentation |

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 .

`data("lrcorrelation")`

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.

```
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]