View source: R/pacotestRVine.R
pacotestRvineSeq | R Documentation |
The function can be used to test the simplifying assumption for R-vine copulas in a sequential manner. Each pair-copula from the second tree on is tested to be a (j-1)-th order partial copula. To apply the function one needs to provide the data and a specified/estimated R-vine copula model in form of a RVineMatrix from the VineCopula-package. Additionally, a pacotest options list, which can be generated with the pacotestset
function, needs to be provided.
pacotestRvineSeq(data, RVM, pacotestOptions, level = 0.05, illustration = 2, stopIfRejected = TRUE)
data |
A (n x d) matrix (or data frame) of [0,1] data (i.e. uniform margins). |
RVM |
An RVineMatrix object (VineCopula-package) which includes the structure, the pair-copula families and parameters of an R-vine copula. |
pacotestOptions |
A options list generated by the |
level |
The level of the test. |
illustration |
Either 1 or 2. If illustration = 1, the p-value for each test for a (j-1)-th order partial copula is displayed. If illustration = 2, a progress information is displayed for each tree. It consists of the individual test level and the number of H0 rejections. |
stopIfRejected |
A logical variable indicating whether the sequential test procedure should be stopped in the first tree where an H0 for one of the conditional copulas is rejected. |
A list consisting of the following elements:
pacotestResultLists |
A matrix in the same structure like the |
pValues |
A matrix in the same structure like the |
testResultSummary |
A data.frame summarizing the test results.
The first column, |
Malte S. Kurz
Kurz, M. S. and F. Spanhel (2022), "Testing the simplifying assumption in high-dimensional vine copulas", Electronic Journal of Statistics 16 (2), pp. 5226-5276.
Spanhel, F. and M. S. Kurz (2019), "Simplified vine copula models: Approximations based on the simplifying assumption", Electronic Journal of Statistics 13 (1), pp. 1254-1291.
pacotest-package
, pacotest
, pacotestset
, pacotestRvineSingleCopula
# Sample data and R-vine copula selection are taken # from the documentation of RVineStructureSelect # of the VineCopula package. # Obtain sample data data(daxreturns, package ="VineCopula") dataSet = daxreturns[1:750,1:4] # Specify an R-vine copula model # (can be obtained by calling: RVM = VineCopula::RVineStructureSelect(dataSet)) vineStructure = matrix(c(3,4,1,2,0,2,4,1,0,0,1,4,0,0,0,4),4,4) families = matrix(c(0,5,2,2,0,0,2,14,0,0,0,14,0,0,0,0),4,4) par = matrix(c(0,0.8230664,0.1933472,0.6275062, 0,0,0.2350109,1.6619945, 0,0,0,1.599363, 0,0,0,0),4,4) par2 = matrix(c(0,0,11.757700,4.547847, 0,0,17.15717,0, 0,0,0,0,0,0,0,0),4,4) RVM = VineCopula::RVineMatrix(vineStructure, families, par, par2) # Specify a pacotestOptions list: pacotestOptions = pacotestset('CCC') # Test for the simplifying assumption. pacotestResultList = pacotestRvineSeq(dataSet, RVM, pacotestOptions)
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