revdbayes 1.4.9

New features

The function kgaps_post() 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 function dgaps_post() produces random samples from a posterior distribution for the extremal index based on what we 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. dgaps_post() has the same functionality as kgaps_post().

The print method print.evpost avoids printing a long list by printing only the original function call.
The default value of inc_cens in kgaps_post() is now inc_cens = TRUE.
In the (extremely rare) cases where grimshaw_gp_mle() errors or returns an estimate for which the observation information is singular, a fallback function is used, which maximises the log-likelihood using stats::optim()
In the generalised Pareto example in the introductory vignette, it is now noted that for the Gulf of Mexico data a threshold set at the 95% threshold results in only a small number (16) of threshold excesses.
In the GP section of the introductory vignette a link is given to the binomial-GP analysis in the Posterior Predictive Extreme Value Inference vignette.
In the introductory vignette: corrected references to plots as "on the left" when in fact they were below, and corrected "random example" to "random sample".
The microbenchmark results have been reinstated in the "Faster simulation using revdbayes" vignette.
Activated 3rd edition of the testthat package