| gofGetHybrid {gofCopula} | R Documentation |
GetHybrid gof test
Description
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.
Usage
gofGetHybrid(result, p_values = NULL, nsets = NULL)
Arguments
result |
An object of |
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 |
Details
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:
p_n^{hybrid} = \min(q \cdot \min{(p_n^{(1)}, \dots, p_n^{(q)})},
1)
where q is
the number of tests and p_n^{(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.
Value
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 |
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 |
References
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
Examples
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)