evTestC | R Documentation |
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.
evTestC(x, N = 1000)
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. |
More details are available in the second reference. See also Remillard and Scaillet (2009).
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. |
This test was derived under the assumption of continuous margins, which implies that ties occur with probability zero. The presence of ties in the data might substantially affect the approximate p-value.
Rémillard, 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.
evTestK
, evTestA
, evCopula
,
gofEVCopula
, An
.
## 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)))
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