gofGetHybrid: GetHybrid gof test
In gofCopula: Goodness-of-Fit Tests for Copulae

Description Usage Arguments Details Value References Examples

gofGetHybrid computes based on previous test results from this package and on p-values from your own goodness-of-fit tests the hybrid test p-values for the specified testing size.

1	gofGetHybrid(result, p_values = NULL, nsets = NULL)

`result`	An object of `class` gofCOP.
`p_values`	A vector containing different p-values from your own goodness-of-fit tests. If the elements are unnamed, the test results in the output will be labeled with Test_A, Test_B etc.
`nsets`	The desired number of tests to be included in each hybrid test. It should be an integer larger than 1 and smaller or equal than the number of tests given in `result` and `p_values` together. If `nsets` is set NULL (default), all possible testing sizes are calculated.

In most of scenarios for goodness-of-fit tests, including the one for copula models (e.g. Genest et al. (2009)) there exists no single dominant optimal test. Zhang et al. (2015) proposed a hybrid test which performed in their simulation study more desirably compared to the applied single tests.

The p-value is a combination of the single tests in the following way:

pn^(hybrid) = min(q x min(pn^(1), ..., pn^(q)), 1)

where q is the number of tests and pn^(i) the p-value of the test i. It is ensured that the hybrid test is consistent as long as at least one of the tests is consistent.

The computation of the individual p-values is performed as described in the details of this tests. Note that the derivation differs.

An object of the class gofCOP with the components

`method`	a character which informs about the performed analysis
`copula`	the copula tested for
`margins`	the method used to estimate the margin distribution.
`param.margins`	the parameters of the estimated margin distributions. Only applicable if the margins were not specified as `"ranks"` or `NULL`.
`theta`	dependence parameters of the copulae
`df`	the degrees of freedem of the copula. Only applicable for t-copula.
`res.tests`	a matrix with the p-values and test statistics of the hybrid and the individual tests

Zhang, S., Okhrin, O., Zhou, Q., and Song, P.. Goodness-of-fit Test For Specification of Semiparametric Copula Dependence Models. Journal of Econometrics, 193, 2016, pp. 215-233 doi: 10.1016/j.jeconom.2016.02.017

data(IndexReturns2D)

res_2 = gof(x = IndexReturns2D, copula = "normal", 
            tests = c("gofKernel", "gofKendallCvM", "gofWhite"), M = 10)
gofGetHybrid(result = res_2, 
             p_values = c("MyTest" = 0.3, "AnotherTest" = 0.7), nsets = 3)