cvm_2series: Cramer-von Mises Moebius statistics for testing independence...

View source: R/cvm_2series.R

cvm_2seriesR Documentation

Cramer-von Mises Moebius statistics for testing independence between the innovations of 2 series of same length

Description

This function computes the Cramer-von Mises statistics between x(t) and y(t-l), for l=-lag,.., lag, and also the combinations of the p-values of these statistics.

Usage

cvm_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 dependogram for all possible lags.

Value

cvm

Cramer-von Mises statistics for all lags

Wstat

Sum of (unbiased) Cramer-von Mises statistics

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

data(gas)
out <-cvm_2series(gas$xres,gas$yres,3)


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