rhodcca: Detrended Cross-correlation coefficient

Description

Calculates the detrended cross-correlation coefficient for two time series \(y1\) and \(y2\).

Usage

rhodcca(y1, y2, m = 3, nu = 0, overlap = TRUE)

Arguments

y1, y2

vectors corresponding to the time series data. If \(length(y1)\) and \(length(y2)\) differ, the longer time series is coerced to match the lenght of the shorter.

an integer value or a vector of integer values indicating the size of the window for the polinomial fit. \(min(m)\) must be greater or equal than \(nu\) or else it will return an error.

the degree of the polynomial fit

overlap

logical: if true (the default), uses overlapping windows. Otherwise, non-overlapping boxes are applied.

Value

A list containing the following elements, calculated considering windows of size \(m+1\), for each \(m\) supplied:

F2dfa1, F2dfa2

The detrended variances for \(y1\) and \(y2\), respectively.

Fdcca

The detrended cross-covariance.

rhodcca

The detrended cross-correlation coefficient.

References

Prass, T.S. and Pumi, G. (2019). On the behavior of the DFA and DCCA in trend-stationary processes <arXiv:1910.10589>.

Examples

Run this code

# NOT RUN {
y1 = rnorm(100)
y2 = rnorm(100)
rho.dccam1 = rhodcca(y1, y2, m = 3, nu = 0, overlap = TRUE)
rho.dccam1

rho.dccam2 = rhodcca(y1, y2, m = c(3,6,8), nu = 0, overlap = TRUE)
rho.dccam2
# }