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:
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.