copula: exchTest – R documentation

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exchTest

Test of Exchangeability for a Bivariate Copula

Description

Test for assessing the exchangeability of the underlying bivariate copula based on the empirical copula. The test statistics are defined in the first two references. Approximate p-values for the test statistics are obtained by means of a multiplier technique if there are no ties in the component series of the bivariate data, or by means of an appropriate bootstrap otherwise.

Usage

exchTest(x, N = 1000, ties = NA,
         ties.method = eval(formals(rank)$ties.method), m = 0)

Arguments

`x`	a data matrix that will be transformed to pseudo-observations.
`N`	number of multiplier or boostrap iterations to be used to simulate realizations of the test statistic under the null hypothesis.
`ties`	logical; if `FALSE`, approximate p-values are computed by means of a multiplier bootstrap; if `TRUE`, a boostrap adapted to the presence of ties in any of the coordinate samples of `x` is used; the default value of `NA` indicates that the presence/absence of ties will be checked for automatically.
`ties.method`	string specifying how ranks should be computed if there are ties in any of the coordinate samples of `x`; passed to `pobs`.
`m`	if `m=0`, integration in the Cramér–von Mises statistic is carried out with respect to the empirical copula; if `m > 0`, integration is carried out with respect to the Lebesgue measure and `m` specifies the size of the integration grid.

Details

More details are available in the references.

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.

References

Genest, C., G. Nešlehová, J. and Quessy, J.-F. (2012). Tests of symmetry for bivariate copulas. Annals of the Institute of Statistical Mathematics 64, 811–834.

Kojadinovic, I. and Yan, J. (2012). A nonparametric test of exchangeability for extreme-value and left-tail decreasing bivariate copulas. The Scandinavian Journal of Statistics 39:3, 480–496.

Kojadinovic, I. (2017). Some copula inference procedures adapted to the presence of ties. Computational Statistics and Data Analysis 112, 24–41, https://arxiv.org/abs/1609.05519.

Examples

## Data from an exchangeable copulas
exchTest(rCopula(200,  gumbelCopula(3)))
exchTest(rCopula(200, claytonCopula(3)))

## An asymmetric Khoudraji-Clayton copula
kc <- khoudrajiCopula(copula1 = indepCopula(),
                      copula2 = claytonCopula(6),
                      shapes = c(0.4, 0.95))
exchTest(rCopula(200, kc))

copula

Multivariate Dependence with Copulas

v1.0-1

GPL (>= 3) | file LICENCE

Authors

Marius Hofert [aut] (<https://orcid.org/0000-0001-8009-4665>), Ivan Kojadinovic [aut] (<https://orcid.org/0000-0002-2903-1543>), Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Jun Yan [aut] (<https://orcid.org/0000-0003-4401-7296>), Johanna G. Nešlehová [ctb] (evTestK(), <https://orcid.org/0000-0001-9634-4796>), Rebecca Morger [ctb] (fitCopula.ml(): code for free mixCopula weight parameters)

Initial release

2020-12-07