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/s1068701502215> and Berghaus and Bucher (2018) <doi:10.1214/17AOS1621>. 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 interexceedance times (Ferro and Segers (2003) <doi:10.1111/14679868.00401>). Three versions of this type of approach are provided: the iterated weight least squares approach of Suveges (2007) <doi:10.1007/s1068700700342>, the Kgaps model of Suveges and Davison (2010) <doi:10.1214/09AOAS292> and a similar approach of Holesovsky, J. and Fusek, M. (2020) <doi:10.1007/s10687020003743> that we refer to as Dgaps. For the Kgaps and Dgaps 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 rightcensored interexceedance times. Graphical diagnostics for the threshold level and the respective tuning parameters K and D are provided.
Package details 


Author  Paul J. Northrop [aut, cre, cph], Constantinos Christodoulides [aut, cph] 
Maintainer  Paul J. Northrop <p.northrop@ucl.ac.uk> 
License  GPL (>= 2) 
Version  1.2.1 
URL  https://github.com/paulnorthrop/exdex https://paulnorthrop.github.io/exdex/ 
Package repository  View on CRAN 
Installation 
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