High-Performance Open-Source Archive
New function measures_nonsimplifyingness_NP for the
estimation of the non-parametric measures of non-simplifyingness for
conditional copulas, introduced in arXiv:2504.07704.
Add more explicit warnings in estimateNPCondCopula
when the bandwidth h is too small. This should reduce the
total number of warnings there when using too small bandwidth. The
previous behavior was the following: there would be 1 warning per value
of X3 such that the total sum of kernel-based weights is 0.
The new behavior is the following: there is 1 warning per call of
estimateNPCondCopula.
Inputs Z and newZ to
CKT.kernel can be of class data.frame,
provided that all the entries are numeric (and that the dimensions
match).
Add option warnNA = FALSE to CKT.kernel
for not raising warnings if some of the estimated conditional Kendall’s
tau are NAs. The corresponding warning has also been
improved and is more explicit about the number of NAs
produced, in particular, if the input already contained
NAs.
CKT.kernel now returns an S3 object of
class estimated_CKT_kernel with se,
confint and plot methods.
In case of cross-validation, CKT.kernel also returns
the result of the corresponding function (CKT.hCV.l1out or
CKT.hCV.Kfolds).
New option nPairs = "all" in
CKT.hCV.l1out to use all possible pairs. Also available in
CKT.kernel if CKT.hCV.l1out is chosen as the
cross-validation method.
New S3 generic se for the standard errors. Currently
only used for objects returned by simpA.kendallReg and
CKT.kernel.
In simpA.NP and simpA.param, the
parameter truncVal used to have no effect (contrary to what
was written in the documentation). It is now taken into account. Also it
is now checked that this parameter belongs to the interval
[0, 1/2) so that the integration interval is not
empty.
In simpA.NP and simpA.param, the
weights involved in the Gaussian quadrature have been fixed to
correspond to the correct integration interval.
Fix a bug in simpA.NP for computation of the
integration-based test statistics T1_CvM_Cs3,
T1_CvM_Cs4, tilde_T0_CvM, which were incorrect
of a constant factor. P-values were unaffected by this bug, as the
constant factor was also present in the bootstrap test
statistic.
Some errors occurring in CKT.kernel with a
multivariate Z and small bandwidth have been
fixed.
Fix bug in computation of the standard errors in
simpA.kendallReg. This affected also the corresponding
p-values of each estimated coefficients (but not the p-value of the
Wald-type test which are computed in another way).
NOTE:
Found the following (possibly) invalid URLs:
URL: https://arxiv.org/pdf/2204.03285.pdf (moved to http://arxiv.org/pdf/2204.03285) From: README.md Status: 301 Message: Moved Permanently For content that is ‘Moved Permanently’, please change http to https, add trailing slashes, or replace the old by the new URL.
Argument names have been shortened: functions taking arguments of
the form observedX1 = are now simplified to
X1 = ... (which was already an interface present for some
of the functions of the package).
Errors because of inputs of different lengths (for example
computing some kind of dependence between two vectors X1
and X2 of different lengths) are now of the class
DifferentLengthsError. Their messages now explicitly give
the lengths of the different objects.
Function CKT.kernel can now handle arguments
X1, X2 and Z in the case where
these are matrices with 1 column.
Function simpA.kendallReg can handle the case where
only one regressor is given. It also uses stats::lm.fit for
the unpenalized regression. A typo in the Wald test statistic has been
fixed. Its output is an S3 object of class
simpA_kendallReg_test with print,
plot, coef, and vcov
methods.
Function CKT.kernel has now more options to control
the possible display of the progress bar to show the progress of the
computation.
New dependency: testthat has been added to
Suggests.
New dependency: DiagrammeR has been added to
Suggests (for nice plotting of the tree generated by
bCond.treeCKT). This package was already suggested by
data.tree (which is imported).
Fix CRAN NOTE:
Found the following Rd file(s) with Rd targets missing package anchors:
estimateParCondCopula.Rd: VineCopula
Please provide package anchors for all Rd targets not in the package itself and the base packages.
Adding a warning to CKT.kernel() when some estimated
conditional Kendall’s taus are NA because of a too small
bandwidth.
Fixing a bug for CKT.kernel() when the conditioning
variable is multivariate.
Adding and updating references for conditional copulas with discretized conditioning events.
Fix an error when running
bCond.simpA.CKT().
Fix default value of the argument minSize in
bCond.treeCKT() to be
minSize = minProb * nrow(XI) as intended.
Functions CKT.kernel() and
CKT.estimate() now warn and return numeric(0)
when the argument newZ is numeric(0).
New dependence wdm instead of pcaPP for
fast computation of Kendall’s tau.
Functions CKT.kernel, CKT.hCV.l1out,
CKT.hCV.Kfolds and CKTmatrix.kernel gain a new
choice "wdm" for the argument typeEstCKT. This
new choice allows for faster computation using the package
wdm. For observations without ties, it is equivalent to the
previous choice typeEstCKT = 4.
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