DFA (version 0.1.0)

Deltarho: Deltarho

Description

Applies the Detrended Cross-Correlation Coefficient Difference (Deltarho) to time series.

Usage

Deltarho(file,file2,file3,file4,m=1)

Arguments

file

Univariate time series (must be a vector)

file2

Univariate time series (must be a vector)

file3

Univariate time series (must be a vector)

file4

Univariate time series (must be a vector)

m

An integer of the polynomial order for the detrending (by default m=1).

Value

box_size

Size of the windows computed in a geometric scale.

Log_n

decimal logarithmic of the box size.

DFA1

decimal logarithmic fluctuation function of the first time series.

DFA2

decimal logarithmic fluctuation function of the second time series.

DFA3

decimal logarithmic fluctuation function of the third time series.

DFA4

decimal logarithmic fluctuation function of the fourth time series.

DCCA1

Detrended Cross-Correlation function between the first and the second time series.

DCCA2

Detrended Cross-Correlation function between the third and the fourth time series.

rhoDCCA1

Detrended Cross-Correlation Coefficient function between the first and the second time series.

rhoDCCA2

Detrended Cross-Correlation Coefficient function between the third and the fourth time series.

Details

The Deltarho is computed in a geometric scale.

References

SILVA, Marcus Fernandes da et al. Quantifying cross-correlation between ibovespa and brazilian blue-chips: The dcca approach. Physica A: Statistical Mechanics and its Applications, v. 424,2015.

Examples

# NOT RUN {
library(DFA)
data("data1")
data("data2")
data("data3")
data("data4")
file = data1
file2= data2
file3= data3
file4= data4

Deltarho(file,file2,file3,file4,m=1)
# }
# NOT RUN {
# Example with different polynomial order.

library(DFA)
file = rnorm(100)
file2= rnorm(100)
file3= rnorm(100)
file4= rnorm(100)

Deltarho(file,file2,file3,file4,m=4)

# }
# NOT RUN {
# }