IndGenErrors (version 0.1.6)

crosscor_3series: Cross-correlations statistics for testing independence between the innovations of 3 series of same length

Description

This function computes the cross-correlations for all lags = -lag2, .. lag2, for all pairs, and for pair of lags = (-lag3,-lag3),...(lag3,lag3) for the three series.

Usage

crosscor_3series(x, y, z, lag2, lag3)

Value

stat

Cross-correlations for all lags and for all subsets

H

Sum of squares of cross-correlations for all subsets

pvalue

P-value of stat for all subsets and H

n

length of the time series

Arguments

x

Pseudo-observations (or residuals) of first series.

y

Pseudo-observations (or residuals) of second series.

z

Pseudo-observations (or residuals) of third series.

lag2

Maximum number of lags around 0 for pairs of series.

lag3

Maximum number of lags around 0 for the three series.

References

Duchesne, Ghoudi & Remillard (2012). On Testing for independence between the innovations of several time series. CJS, vol. 40, 447-479.

Examples

# Romano-Siegel's example #
data(romano_ex)
outr = crosscor_3series(romano_ex$x,romano_ex$y,romano_ex$z,5,2)