SlidingWindows (version 0.2.0)

dmc.SlidingWindows: Detrended multiple cross-correlation coefficient with sliding windows.

Description

This function generates DMC Coefficient of three time series with sliding windows approach.

Usage

dmc.SlidingWindows(x1, x2, y, w = 98, k = 10, method = "rhodcca", nu = 0)

Arguments

x1

A vector containing univariate time series.

x2

A vector containing univariate time series.

y

A vector containing univariate time series.

w

An integer value indicating the window size \(w < length(y)\). If \(w = length(y)\), will be computed the function will not slide.

k

An integer value indicating the boundary of the division \((N/k)\). The smallest value of \(k\) is \(4\).

method

A character string indicating which correlation coefficient is to be used. If method = "rhodcca" (default) the dmc coefficient is generated from the DCCA coefficient. If method = "dmca", the dmc coefficient is generated from the DMCA coefficient.

nu

An integer value. See the DCCA package.

Value

A list containing "w", "dmc", "yx1", "yx2", "x1x2".

Details

This function include following measures: w, timescale, dmc and cross-correlation between: yx1, yx2, x1x2

References

ZEBENDE, G.; SILVA-FILHO, A.M. Detrended multiple cross-correlation coefficient, Physica A 510, 91-97, 2018. doi="doi.org/10.1016/j.physa.2018.06.119".

GUEDES,E.F.;SILVA-FILHO, A.M.; ZEBENDE, G.F. Detrended multiple cross-correlation coefficient with sliding windows approach. Physica A, 125990, 2021. doi="doi.org/10.1016/j.physa.2021.125990".

Examples

# NOT RUN {
x1 <- rnorm(100)
x2 <- rnorm(100)
y <- rnorm(100)
dmc.SlidingWindows(x1,x2,y,w=99,k=10,nu=0, method="rhodcca")
dmc.SlidingWindows(x1,x2,y,w=99,k=10,nu=0, method="dmca")

# }