Package: extrememix 0.0.1
Manuele Leonelli
extrememix: Bayesian Estimation of Extreme Value Mixture Models
Fits extreme value mixture models, which are models for tails not requiring selection of a threshold, for continuous data. It includes functions for model comparison, estimation of quantity of interest in extreme value analysis and plotting. Reference: CN Behrens, HF Lopes, D Gamerman (2004) <doi:10.1191/1471082X04st075oa>. FF do Nascimento, D. Gamerman, HF Lopes <doi:10.1007/s11222-011-9270-z>.
Authors:
extrememix_0.0.1.tar.gz
extrememix_0.0.1.zip(r-4.5)extrememix_0.0.1.zip(r-4.4)extrememix_0.0.1.zip(r-4.3)
extrememix_0.0.1.tgz(r-4.4-x86_64)extrememix_0.0.1.tgz(r-4.4-arm64)extrememix_0.0.1.tgz(r-4.3-x86_64)extrememix_0.0.1.tgz(r-4.3-arm64)
extrememix_0.0.1.tar.gz(r-4.5-noble)extrememix_0.0.1.tar.gz(r-4.4-noble)
extrememix_0.0.1.tgz(r-4.4-emscripten)extrememix_0.0.1.tgz(r-4.3-emscripten)
extrememix.pdf |extrememix.html✨
extrememix/json (API)
NEWS
| # Install 'extrememix' in R: |
| install.packages('extrememix', repos = c('https://manueleleonelli.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/manueleleonelli/extrememix/issues
- rainfall - Monthly Maxima Daily Rainfall in Madrid
- rainfall_ggpd - Rainfall FGGPD Output
- rainfall_mgpd - Rainfall FMGPD Output
Last updated 2 days agofrom:5ac20adb0d. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 21 2024 |
| R-4.5-win-x86_64 | OK | Oct 21 2024 |
| R-4.5-linux-x86_64 | OK | Oct 21 2024 |
| R-4.4-win-x86_64 | OK | Oct 21 2024 |
| R-4.4-mac-x86_64 | OK | Oct 21 2024 |
| R-4.4-mac-aarch64 | OK | Oct 21 2024 |
| R-4.3-win-x86_64 | OK | Oct 21 2024 |
| R-4.3-mac-x86_64 | OK | Oct 21 2024 |
| R-4.3-mac-aarch64 | OK | Oct 21 2024 |
Exports:check_convergencedggpdDICdmgammadmgpdESfggpdfmgpdpggpdpmgammapmgpdpredqggpdqmgammaqmgpdquantreturn_levelrggpdrmgammarmgpdupper_boundVaRWAIC
Dependencies:abindaskpassbackportsbase64encbayesplotbslibcachemchandwichcheckmateclicolorspacecpp11crosstalkcurldata.tabledigestdistributionaldplyrevaluateevdexdexfansifarverfastmapfontawesomefsgenericsggplot2ggridgesgluegridExtragtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemixtoolsmunsellnlmenumDerivopensslpillarpkgconfigplotlyplyrposteriorpromisespurrrR6rappdirsRColorBrewerRcppRcppArmadilloRcppProgressRcppRollreshape2revdbayesrlangrmarkdownrustsassscalessegmentedstringistringrsurvivalsystensorAthreshrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convergence Assessment of MCMC Algorithms | check_convergence check_convergence.evmm |
| Deviance Information Criterion | DIC DIC.evmm |
| Expected Shortfall | ES ES.evmm |
| GGPD Estimation | fggpd |
| MGPD Estimation | fmgpd |
| The GGPD distribution | dggpd ggpd pggpd qggpd rggpd |
| Log-likelihood Method | logLik.evmm |
| The Gamma Mixture Distribution | dmgamma mgamma pmgamma qmgamma rmgamma |
| The MGPD distribution | dmgpd mgpd pmgpd qmgpd rmgpd |
| Plot Methods for Summaries | plot.ES plot.quant plot.return_level plot.VaR plot_summaries |
| Plot of Extreme Value Mixture Models | plot.evmm |
| Plot Upper Bounds | plot.upper_bound |
| Predictive Distribution | pred pred.evmm |
| Printing Methods | print print.ES print.evmm print.quantile print.return_level print.summary.ggpd print.upper_bound print.VaR |
| Estimated Quantiles | quant quant.evmm |
| Monthly Maxima Daily Rainfall in Madrid | rainfall |
| Rainfall FGGPD Output | rainfall_ggpd |
| Rainfall FMGPD Output | rainfall_mgpd |
| Return Levels | return_level return_level.evmm |
| Summary Method | summary.evmm |
| Upper Bound | upper_bound upper_bound.evmm |
| Value-at-Risk | VaR VaR.evmm |
| Widely Applicable Information Criteria | WAIC WAIC.evmm |