Package: fExtremes 4032.84
Paul J. Northrop
fExtremes: Rmetrics - Modelling Extreme Events in Finance
Provides functions for analysing and modelling extreme events in financial time Series. The topics include: (i) data pre-processing, (ii) explorative data analysis, (iii) peak over threshold modelling, (iv) block maxima modelling, (v) estimation of VaR and CVaR, and (vi) the computation of the extreme index.
Authors:
fExtremes_4032.84.tar.gz
fExtremes_4032.84.zip(r-4.5)fExtremes_4032.84.zip(r-4.4)fExtremes_4032.84.zip(r-4.3)
fExtremes_4032.84.tgz(r-4.4-any)fExtremes_4032.84.tgz(r-4.3-any)
fExtremes_4032.84.tar.gz(r-4.5-noble)fExtremes_4032.84.tar.gz(r-4.4-noble)
fExtremes_4032.84.tgz(r-4.4-emscripten)fExtremes_4032.84.tgz(r-4.3-emscripten)
fExtremes.pdf |fExtremes.html✨
fExtremes/json (API)
NEWS
| # Install 'fExtremes' in R: |
| install.packages('fExtremes', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/rmetrics
- bmwRet - Time Series Data Sets
- danishClaims - Time Series Data Sets
Last updated 7 days agofrom:8f3970af90. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 14 2024 |
| R-4.5-win | OK | Dec 14 2024 |
| R-4.5-linux | OK | Dec 14 2024 |
| R-4.4-win | OK | Dec 14 2024 |
| R-4.4-mac | OK | Dec 14 2024 |
| R-4.3-win | OK | Dec 14 2024 |
| R-4.3-mac | OK | Dec 14 2024 |
Exports:.gevmleFit.gevpwmFit.gevrlevelLLH.gummleFit.gumpwmFitblockMaximablockThetaclusterThetaCVaRdeClusterdgevdgpdemdPlotexindexesPlotexindexPlotferrosegersThetafindThresholdgevFitgevMomentsgevrlevelPlotgevSimgevSliderghMeanExcessFitghtMeanExcessFitgpdFitgpdMomentsgpdQPlotgpdQuantPlotgpdRiskMeasuresgpdSfallPlotgpdShapePlotgpdSimgpdSlidergpdTailPlotgumbelFitgumbelSimhillPlothypMeanExcessFitlilPlotmePlotmrlPlotmsratioPlotmxfPlotnigMeanExcessFitnormMeanExcessFitpgevpgpdpointProcessqgevqgpdqqparetoPlotrecordsPlotrgevrgpdrunThetashaparmDEHaanshaparmHillshaparmPickandsshaparmPlotsllnPlotssrecordsPlottailPlottailRisktailSliderthetaSimVaRxacfPlot
Dependencies:cvarfastICAfBasicsfGarchgbutilsgsslatticeMASSMatrixrbibutilsRdpackspatialstabledisttimeDatetimeSeries
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Modelling Extreme Events in Finance | fExtremes-package fExtremes |
| Extremes Data Preprocessing | blockMaxima DataPreprocessing deCluster findThreshold pointProcess |
| Extremal Index Estimation | blockTheta clusterTheta exindexesPlot exindexPlot ExtremeIndex ferrosegersTheta fTHETA fTHETA-class runTheta show,fTHETA-method thetaSim |
| Explorative Data Analysis | emdPlot ExtremesData ghMeanExcessFit ghtMeanExcessFit hypMeanExcessFit lilPlot mePlot mrlPlot msratioPlot mxfPlot nigMeanExcessFit normMeanExcessFit qqparetoPlot recordsPlot sllnPlot ssrecordsPlot xacfPlot |
| Generalized Extreme Value Distribution | dgev GevDistribution gevMoments gevSlider pgev qgev rgev |
| Generalized Extreme Value Modelling | GevMdaEstimation hillPlot shaparmDEHaan shaparmHill shaparmPickands shaparmPlot |
| Generalized Extreme Value Modelling | fGEVFIT fGEVFIT-class gevFit GevModelling gevSim gumbelFit gumbelSim plot.fGEVFIT show,fGEVFIT-method summary.fGEVFIT |
| Generalized Extreme Value Modelling | GevRisk gevrlevelPlot |
| Generalized Pareto Distribution | dgpd GpdDistribution gpdMoments gpdSlider pgpd qgpd rgpd |
| GPD Distributions for Extreme Value Theory | fGPDFIT fGPDFIT-class gpdFit GpdModelling gpdSim plot.fGPDFIT show,fGPDFIT-method summary.fGPDFIT |
| GPD Distributions for Extreme Value Theory | gpdQPlot gpdQuantPlot gpdRisk gpdRiskMeasures gpdSfallPlot gpdShapePlot gpdTailPlot tailPlot tailRisk tailSlider |
| Time Series Data Sets | bmwRet danishClaims TimeSeriesData |
| Value-at-Risk | CVaR ValueAtRisk VaR |
