Packaged: 2018-01-26 14:56:30 UTC; davidbolin

Description: Functions that compute probabilistic excursion sets, contour credibility regions, contour avoiding regions, and simultaneous confidence bands for latent Gaussian random processes and fields. The package also contains functions that calculate these quantities for models estimated with the INLA package. The main references for excursions are Bolin and Lindgren (2015) <doi:10.1111/rssb.12055> and Bolin and Lindgren (2017) <doi:10.1080/10618600.2016.1228537>. These can be generated by the citation function in R.
Packaged: 2018-01-28 12:42:13 UTC; davidbolin

Packaged: 2018-04-03 10:54:24 UTC; davidbolin

person("David", "Bolin", email = "davidbolin@gmail.com", role = c("cre", "aut")),
person("Finn", "Lindgren", email = "finn.lindgren@gmail.com", role = "aut"))
Packaged: 2018-07-19 15:02:33 UTC; davidbolin

Description: Functions that compute probabilistic excursion sets, contour credibility regions, contour avoiding regions, and simultaneous confidence bands for latent Gaussian random processes and fields. The package also contains functions that calculate these quantities for models estimated with the INLA package. The main references for excursions are Bolin and Lindgren (2015) <doi:10.1111/rssb.12055>, Bolin and Lindgren (2017) <doi:10.1080/10618600.2016.1228537>, and Bolin and Lindgren (2018) <doi:10.18637/jss.v086.i05>. These can be generated by the citation function in R.
Packaged: 2018-08-31 10:14:04 UTC; davidbolin

Suggests: INLA (>= 0.0-1468840039), testthat, rgeos, rgdal
Imports: graphics, methods, stats, withr

Suggests: INLA (>= 21.08.31), testthat, rgeos, rgdal

Suggests: INLA (>= 21.08.31), testthat (>= 3.0.0), rgeos, rgdal

SystemRequirements: Gnu Scientific Library version >= 2.1
from the SuiteSparse collection of Tim Davis, and the
RngStreams library by Pierre L'Ecuyer.  For details see the

person("Constantinos", "Christodoulides", role = c("aut", "cph"))
Description: 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. The other type of methodology
uses a model for the distribution of threshold inter-exceedance times
versions of this type of approach are provided, following Suveges (2007)
Imports: chandwich, graphics, methods, Rcpp, RcppRoll, stats
Suggests: knitr, revdbayes, rmarkdown, testthat, zoo (>= 1.6.4)