cvm_3series: Cramer-von Mises Moebius statistics for testing independence...

In IndGenErrors: Tests of Independence Between Innovations of Generalized Error Models

Cramer-von Mises Moebius statistics for testing independence between the innovations of 3 series of same length

Description

This function computes the Cramer-von Mises statistics between x(t), y(t-l2), z(t-l3), for l2=-lag2,.., lag2, l3=-lag3,.., lag3,and also the combinations of these statistics.

Usage

cvm_3series(x, y, z, lag2, lag3)

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.

Value

cvm	Cramer-von Mises statistics for all lags and for all subsets
Wstat	Sum of (unbiased) Cramer-von Mises statistics for all subsets
Fstat	Combination of p-values of the Cramer-von Mises statistics
pvalue	List of p-values for the cvm, Wstat, and Fstat

References

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

Examples

set.seed(1)
x0 = rnorm(100); y = rnorm(100); z = rnorm(100);

IndGenErrors documentation built on July 9, 2023, 6:46 p.m.