lite: Likelihood-Based Inference for Time Series Extremes
Performs likelihood-based inference for stationary time series
extremes. The general approach follows Fawcett and Walshaw (2012)
<doi:10.1002/env.2133>. Marginal extreme value inferences are adjusted for
cluster dependence in the data using the methodology in Chandler and Bate
(2007) <doi:10.1093/biomet/asm015>, producing an adjusted log-likelihood
for the model parameters. A log-likelihood for the extremal index is
produced using the K-gaps model of Suveges and Davison (2010)
<doi:10.1214/09-AOAS292>. These log-likelihoods are combined to make
inferences about return levels.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
chandwich, exdex, graphics, revdbayes, sandwich, stats |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2022-04-08 |
| Author: |
Paul J. Northrop [aut, cre, cph] |
| Maintainer: |
Paul J. Northrop <p.northrop at ucl.ac.uk> |
| BugReports: |
https://github.com/paulnorthrop/lite/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://paulnorthrop.github.io/lite/,
https://github.com/paulnorthrop/lite |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
lite results |
Documentation:
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