withEstUncert = TRUE and
estUncertWithRanks = TRUE. Before, up to version 0.3.1,
both parameters defaulted to FALSE.pacotest(U,W,'CCC'), the default
options for the CCC test are used (cf. pacotestset), but
the two parameters withEstUncert = FALSE and
estUncertWithRanks = FALSE are altered. In contrast when
calling pacotestOptions = pacotestset('CCC'), the two
parameters are set to withEstUncert = TRUE and
estUncertWithRanks = TRUE. For the CCC test, under the
default setting, it is assumed that estimated PPITs are provided and the
test statistic is computed under consideration of estimation uncertainty
of the probability integral transforms, i.e.,
withEstUncert = TRUE and
estUncertWithRanks = TRUE. To apply pacotest
with withEstUncert = TRUE, three additional inputs have to
be provided (data, svcmDataFrame and
cPitData).pacotestRvineSeq or
pacotestRvineSingleCopula instead of pacotest.
These functions automatically pass through the additional arguments
data, svcmDataFrame and cPitData
to the function pacotest and the CCC test can be applied in
its default setting with consideration of estimation uncertainty of the
probability integral transforms, i.e., withEstUncert = TRUE
and estUncertWithRanks = TRUE.ECORR test to CCC test to be
in line with the corresponding paper (Kurz and Spanhel (2017) https://arxiv.org/abs/1706.02338)testResultSummary, to pacotestRvineSeq()stopIfRejected, added to
pacotestRvineSeq(), which allows the user to stop the
sequential test procedure in case of a rejectionpacotestRvineSeq()aggInfo is now set to
meanAll to be in line with the paperextractSubTree; Added a corresponding unit
test
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