GMZTests (version 0.1.4)

dmc.test: Statistical test for Multiple Detrended Cross-Correlation Coefficient

Description

This function performs the statistical test for DMC Cross-Correlation Coefficient based in White Gaussian Noise process.

Usage

dmc.test(N, k, m, method, nu, rep)

Arguments

N

An integer value for the time series length.

k

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

m

an integer value or a vector of integer values indicating the size of the window for the polinomial fit.

method

A character string indicating which correlation coefficient is to be used. If method = "rhodcca" 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.

rep

An integer value indicating the number of repetitions.

Value

An list containing "timescale", parameters of beta distribution: "shape1", "se1","shape2","se2" and confidence interval: "CI_0.90_uppper", "CI_0.95_uppper", "CI_0.99_uppper".

Details

This function include following measures: w, timescale, dmc, rhodcca_yx1, rhodcca_yx2, rhodcca_x1x2

References

SILVA-FILHO,A.M; ZEBENDE,G.; CASTRO,A.P.; GUEDES,E. Statistical test for multiple detrended cross-correlation coefficient, Physica A, v.562, 125285, 2021.

KRISTOUFEK, L. Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series. PHYSICA A, v.406, p.169-175, 2014.

Examples

# NOT RUN {
dmc.test(N=100, k=10, m=c(4:6), method="rhodcca", nu=0, rep=10)
dmc.test(N=100, k=10, m=c(4:6), method="dmca", nu=0, rep=10)

# }