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
#)