copula (version 0.999-19.1)

evTestC: Large-sample Test of Multivariate Extreme-Value Dependence

Description

Test of multivariate extreme-value dependence based on the empirical copula and max-stability. The test statistics are defined in the second reference. Approximate p-values for the test statistics are obtained by means of a multiplier technique.

Usage

evTestC(x, N = 1000)

Arguments

x

a data matrix that will be transformed to pseudo-observations.

N

number of multiplier iterations to be used to simulate realizations of the test statistic under the null hypothesis.

Value

An object of class htest which is a list, some of the components of which are

statistic

value of the test statistic.

p.value

corresponding approximate p-value.

Details

More details are available in the second reference. See also Remillard and Scaillet (2009).

References

R<U+00E9>millard, B. and Scaillet, O. (2009). Testing for equality between two copulas. Journal of Multivariate Analysis, 100(3), pages 377-386.

Kojadinovic, I., Segers, J., and Yan, J. (2011). Large-sample tests of extreme-value dependence for multivariate copulas. The Canadian Journal of Statistics 39, 4, pages 703-720.

See Also

evTestK, evTestA, evCopula, gofEVCopula, An.

Examples

# NOT RUN {
## Do these data come from an extreme-value copula?
evTestC(rCopula(200, gumbelCopula(3)))
evTestC(rCopula(200, claytonCopula(3)))

## Three-dimensional examples
evTestC(rCopula(200, gumbelCopula(3, dim=3)))
evTestC(rCopula(200, claytonCopula(3, dim=3)))
# }