exdex

Performs frequentist inference for the extremal index of a stationary time series. Two types of methodology are used. One type is based on a model that relates the distribution of block maxima to the marginal distribution of series and leads to the semiparametric maxima estimators described in Northrop (2015) doi:10.1007/s10687-015-0221-5 and Berghaus and Bucher (2018) doi:10.1214/17-AOS1621. Sliding block maxima are used to increase precision of estimation. A graphical block size diagnostic is provided. The other type of methodology uses a model for the distribution of threshold inter-exceedance times (Ferro and Segers (2003) doi:10.1111/1467-9868.00401). Three versions of this type of approach are provided: the iterated weight least squares approach of Suveges (2007) doi:10.1007/s10687-007-0034-2, the K-gaps model of Suveges and Davison (2010) doi:10.1214/09-AOAS292 and a similar approach of Holesovsky and Fusek (2020) doi:10.1007/s10687-020-00374-3 that we refer to as D-gaps. For the K-gaps and D-gaps models this package allows missing values in the data, can accommodate independent subsets of data, such as monthly or seasonal time series from different years, and can incorporate information from right-censored inter-exceedance times. Graphical diagnostics for the threshold level and the respective tuning parameters K and D are provided.

Last 30 days

This package has been downloaded 520 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 14 times.

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Last 365 days

This package has been downloaded 7,141 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Jul 24, 2024 with 66 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.