Nothing
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 testAny scripts or data that you put into this service are public.
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