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Characterisation of the extremal dependence structure of time series, avoiding pre-processing and filtering as done typically with peaks-over-threshold methods. It uses the conditional approach of Heffernan and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x> which is very flexible in terms of extremal and asymptotic dependence structures, and Bayesian methods improve efficiency and allow for deriving measures of uncertainty. For example, the extremal index, related to the size of clusters in time, can be estimated and samples from its posterior distribution obtained.
| Version: | 0.3.3 |
| Imports: | evd, mvtnorm, stats, MASS, graphics, tictoc |
| Published: | 2021-04-23 |
| Author: | Thomas Lugrin |
| Maintainer: | Thomas Lugrin <thomas.lugrin at alumni.epfl.ch> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Citation: | tsxtreme citation info |
| Materials: | README NEWS |
| CRAN checks: | tsxtreme results |
| Reference manual: | tsxtreme.pdf |
| Package source: | tsxtreme_0.3.3.tar.gz |
| Windows binaries: | r-devel: tsxtreme_0.3.3.zip, r-release: tsxtreme_0.3.3.zip, r-oldrel: tsxtreme_0.3.3.zip |
| macOS binaries: | r-release (arm64): tsxtreme_0.3.3.tgz, r-oldrel (arm64): tsxtreme_0.3.3.tgz, r-release (x86_64): tsxtreme_0.3.3.tgz, r-oldrel (x86_64): tsxtreme_0.3.3.tgz |
| Old sources: | tsxtreme archive |
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