Package: tsxtreme 0.3.3
tsxtreme: Bayesian Modelling of Extremal Dependence in Time Series
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.
Authors:
tsxtreme_0.3.3.tar.gz
tsxtreme_0.3.3.zip(r-4.5)tsxtreme_0.3.3.zip(r-4.4)tsxtreme_0.3.3.zip(r-4.3)
tsxtreme_0.3.3.tgz(r-4.4-x86_64)tsxtreme_0.3.3.tgz(r-4.4-arm64)tsxtreme_0.3.3.tgz(r-4.3-x86_64)tsxtreme_0.3.3.tgz(r-4.3-arm64)
tsxtreme_0.3.3.tar.gz(r-4.5-noble)tsxtreme_0.3.3.tar.gz(r-4.4-noble)
tsxtreme_0.3.3.tgz(r-4.4-emscripten)tsxtreme_0.3.3.tgz(r-4.3-emscripten)
tsxtreme.pdf |tsxtreme.html✨
tsxtreme/json (API)
| # Install 'tsxtreme' in R: |
| install.packages('tsxtreme', repos = c('https://tlugrin.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tlugrin/tsxtreme/issues
Last updated 4 years agofrom:9f49d56dff. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 14 2024 |
| R-4.5-win-x86_64 | OK | Oct 14 2024 |
| R-4.5-linux-x86_64 | OK | Oct 14 2024 |
| R-4.4-win-x86_64 | OK | Oct 14 2024 |
| R-4.4-mac-x86_64 | OK | Oct 14 2024 |
| R-4.4-mac-aarch64 | OK | Oct 14 2024 |
| R-4.3-win-x86_64 | OK | Oct 14 2024 |
| R-4.3-mac-x86_64 | OK | Oct 14 2024 |
| R-4.3-mac-aarch64 | OK | Oct 14 2024 |
Exports:bayesparamschifitdep2fitdepfitdlaplis.bayesfitis.bayesparamsis.depmeasureis.stepfitplaplqlaplrlaplstepfittheta2fitthetafitthetaruns
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Modelling of Extremal Dependence in Time Series | tsxtreme-package tsxtreme |
| Traces from MCMC output | bayesfit is.bayesfit plot.bayesfit print.bayesfit summary.bayesfit |
| Parameters for the semi-parametric approach | bayesparams is.bayesparams print.bayesparams summary.bayesparams |
| Dependence model fit (stepwise) | dep2fit |
| Dependence model fit | depfit |
| Dependence measures estimates | depmeasure is.depmeasure plot.depmeasure print.depmeasure summary.depmeasure |
| Estimate dependence measures | chifit depmeasures thetafit |
| The Laplace Distribution | dlapl plapl qlapl rlapl |
| Estimates from stepwise fit | is.stepfit plot.stepfit print.stepfit stepfit summary.stepfit |
| Fit time series extremes | theta2fit |
| Runs estimator | thetaruns |
