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@AlexisDerumigny AlexisDerumigny released this 03 Sep 14:49
· 2 commits to main since this release
45b9616

CondCopulas 0.1.4.1

CondCopulas 0.1.4

  • 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 \link{} targets missing package anchors:

      estimateParCondCopula.Rd: VineCopula

      Please provide package anchors for all Rd \link{} targets not in the
      package itself and the base packages.

CondCopulas 0.1.3

  • 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).