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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 extreme values. Both maximum likelihood and Bayesian approaches are available.

Version:1.1.1
Depends:R (≥ 3.3.0)
Imports:chandwich,exdex, graphics,revdbayes,rust,sandwich, stats
Suggests:knitr,rmarkdown,testthat (≥ 3.0.0)
Published:2024-07-17
DOI:10.32614/CRAN.package.lite
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,NEWS
CRAN checks:lite results

Documentation:

Reference manual:lite.html ,lite.pdf
Vignettes:Frequentist Likelihood-Based Inference for Time Series Extremes (source,R code)
Bayesian Likelihood-Based Inference for Time Series Extremes (source,R code)

Downloads:

Package source: lite_1.1.1.tar.gz
Windows binaries: r-devel:lite_1.1.1.zip, r-release:lite_1.1.1.zip, r-oldrel:lite_1.1.1.zip
macOS binaries: r-release (arm64):lite_1.1.1.tgz, r-oldrel (arm64):lite_1.1.1.tgz, r-release (x86_64):lite_1.1.1.tgz, r-oldrel (x86_64):lite_1.1.1.tgz
Old sources: lite archive

Linking:

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