Bug fixes and minor improvements

  • The issue described at https://github.com/RcppCore/Rcpp/issues/1287 has been fixed to avoid WARNINGs from CRAN checks on some platforms. Thank you to Dirk Eddelbuettel for providing the fix so quickly!

  • Fixed issues with the incorrect use of in some Rd files.

Bug fixes and minor improvements

  • If the argument k = 0 is supplied to kgaps() then an estimate of 1 is returned for the extremal index for any input data. For this very special case the estimated standard error associated with this estimate is set to zero and confidence intervals have a width of zero.

  • Corrected a typing error in the description of uprob in the documentation for plot.choose_uk() and plot.choose_ud().

  • The unnecessary C++11 specification has been dropped to avoid a CRAN Package Check NOTE.

  • README.md: Used app.codecov.io as base for codecov link.

  • Create the help file for the package correctly, with alias exdex-package.

New features

  • A new estimator has been implemented, based on what we will call the D-gaps model of Holesovsky, J. and Fusek, M. Estimation of the extremal index using censored distributions. Extremes 23, 197–213 (2020). doi: 10.1007/s10687-020-00374-3

Bug fixes and minor improvements

  • The value returned by nobs.kgaps() was incorrect in cases where there are censored K-gaps that are equal to zero. These K-gaps should not contribute to the number of observations. This has been corrected.

  • In cases where the data used in kgaps are split into separate sequences, the threshold exceedance probability is estimated using all the data rather than locally within each sequence.

  • A logLik method for objects inheriting from class "kgaps" has been added.

  • In the (unexported, internal) function kgaps_conf_int() the limits of the confidence intervals for the extremal index based on the K-gaps model are constrained manually to (0, 1) to avoid problems in calculating likelihood-based confidence intervals in cases where the the log-likelihood is greater than the interval cutoff when theta = 1.

  • In the documentation of the argument k to kgaps() it is noted that in practice k should be no smaller than 1.

  • The function kgaps() also return standard errors based on the expected information.

  • In the package manual related functions have been arranged in sections for easier reading.

  • Activated 3rd edition of the testthat package

New features

  • The functions kgaps(), kgaps_imt() and choose_uk() can now accept a data argument that
    • is a matrix of independent subsets of data, such as monthly or seasonal time series from different years,
    • contains missing values, that is, NAs.
  • A new dataset cheeseboro is included, which is a matrix containing some missing values.
  • In addition to kgaps(), the functions kgaps_imt() and choose_uk() now have an extra argument inc_cens, which allows contributions from censored K-gaps to be included in the log-likelihood for the extremal index.
  • The default value of inc_cens in kgaps() (and in kgaps_imt() and choose_uk()) is now inc_cens = TRUE.

Bug fixes and minor improvements

Bug fixes and minor improvements

  • An overloading ambiguity has been corrected to ensure installation on Solaris.