crossdep_2series {IndGenErrors} | R Documentation |
Cross-dependences for testing independence between the innovations of 2 series of same length
Description
This function computes the cross-dependence between x(t) and y(t-l), for Spearman, van der Waerden and Savage dependence measures, for l=-lag,.., lag, and also the combination (Wald's type) of these statistics.
Usage
crossdep_2series(x, y, lag, graph = TRUE)
Arguments
x |
Pseudo-observations (or residuals) of first series |
y |
Pseudo-observations (or residuals) of second series |
lag |
Maximum number of lags around 0 |
graph |
Set to TRUE for a correlogram for all possible lags. |
Value
stat |
Cross-dependences for all lags |
H |
Sum of squares of cross-dependences |
pvalue |
P-value of H |
subsets |
c(-lag:lag) |
n |
length of the time series |
References
Duchesne, Ghoudi & Remillard (2012). On Testing for independence between the innovations of several time series. CJS, vol. 40, 447-479.
Nasri & Remillard (2024). Tests of independence and randomness for arbitrary data using copula-based covariances. JMVA, vol. 201, 105273.
Examples
data(gas)
outr <-crossdep_2series(gas$xres,gas$yres,3)