TestIndSerCopulaMulti {MixedIndTests}

Statistics and P-values for a test of randomness for a multivariate time series

Description

This function computes Cramer-von Mises statistics from the multilinear copula and their combination for a tests of randomness for p consecutives values of random vectors X(1), ..., X(p). The p-values are computed using Gaussian multipliers.

Usage

TestIndSerCopulaMulti(x, p, trunc.level = 2, B = 1000, graph = FALSE)

Arguments

x

Time series matrix

p

Number of consecutive vectors

trunc.level

Only subsets of cardinality <= trunc.level (default=2) are considered for the Moebius statistics.

B

Number of multipliers samples (default = 1000)

graph

Set to TRUE if one wants the dependogram of P-values for the Moebius statistics

Value

stat

List of Cramer-von Mises statistics cvm, tilde Sn, and test combinations tilde Tn and tilde Tn2 (only pairs), as defined in Nasri(2022).

pvalue

Approximated P-values for the tests using Gaussian multipliers

References

B.R Nasri (2022). Tests of serial dependence for arbitrary distributions

Examples

data(Y)
out <- TestIndSerCopulaMulti(Y,5,5)