Demo of the TSEVA method | Step 1: Argument selection | Step 2: Prepare inputs for TSEVA | Step 3: Run TSEVA | Step 4: Plot results
Package: RtsEva 1.2.0
RtsEva: Performs the Transformed-Stationary Extreme Values Analysis
Adaptation of the 'Matlab' 'tsEVA' toolbox developed by Lorenzo Mentaschi available here: <https://github.com/menta78/tsEva>. It contains an implementation of the Transformed-Stationary (TS) methodology for non-stationary extreme value Analysis (EVA) as described in Mentaschi et al. (2016) <doi:10.5194/hess-20-3527-2016>. In synthesis this approach consists in: (i) transforming a non-stationary time series into a stationary one to which the stationary extreme value theory can be applied; and (ii) reverse-transforming the result into a non-stationary extreme value distribution. 'RtsEva' offers several options for trend estimation (mean, extremes, seasonal) and contains multiple plotting functions displaying different aspects of the non-stationarity of extremes.
Authors:
RtsEva_1.2.0.tar.gz
RtsEva_1.2.0.zip(r-4.7-any)RtsEva_1.2.0.zip(r-4.6-any)RtsEva_1.2.0.zip(r-4.5-any)
RtsEva_1.2.0.tgz(r-4.6-any)RtsEva_1.2.0.tgz(r-4.5-any)
RtsEva_1.2.0.tar.gz(r-4.7-any)RtsEva_1.2.0.tar.gz(r-4.6-any)
RtsEva_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RtsEva/json (API)
| # Install 'RtsEva' in R: |
| install.packages('RtsEva', repos = c('https://alowis.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alowis/rtseva/issues
Datasets:
- ArdecheStMartin - Simulated river discharge of the Ardeche river at Saint Martin d'Ardeche
- DanubeVienna - Simulated river discharge of the Danube river at Vienna
- EbroZaragoza - Simulated river discharge of the Ebro river at Zaragoza
- RhoneLyon - Simulated river discharge of the Rhone river at Lyon
extreme-value-statisticsnon-stationary-environment
Last updated from:b761930150. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 238 | ||
| source / vignettes | OK | 271 | ||
| linux-release | OK | 198 | ||
| macos-release | OK | 151 | ||
| macos-oldrel | OK | 145 | ||
| windows-devel | OK | 215 | ||
| windows-release | OK | 219 | ||
| windows-oldrel | OK | 294 | ||
| wasm-release | OK | 149 |
Exports:check_timeseriescomputeAnnualMaximacomputeMonthlyMaximadeclustpeaksempdisempdislfindMaxinitPercentilesmax_daily_valuetsEasyParseNamedArgstsEstimateAverageSeasonalitytsEvaChangeptstsEvaComputeReturnLevelsGEVtsEvaComputeReturnLevelsGEVFromAnalysisObjtsEvaComputeReturnLevelsGPDtsEvaComputeReturnLevelsGPDFromAnalysisObjtsEvaComputeReturnPeriodsGEVtsEvaComputeReturnPeriodsGPDtsEvaComputeRLsGEVGPDtsEvaComputeTimeRPtsEvaDetrendTimeSeriestsEvaFillSeriestsEvaFindTrendThresholdtsEvaNanRunnigBlowThtsEvaNanRunningMeantsEvaNanRunningPercentilestsEvaNanRunningStatisticstsEvaNanRunningVarianceTsEvaNstsEvaPlotAllRLevelsGEVtsEvaPlotAllRLevelsGPDtsEvaPlotGEVImageScFromAnalysisObjtsEvaPlotGPDImageScFromAnalysisObjtsEvaPlotReturnLevelsGEVtsEvaPlotReturnLevelsGEVFromAnalysisObjtsEvaPlotReturnLevelsGPDtsEvaPlotReturnLevelsGPDFromAnalysisObjtsEvaPlotSeriesTrendStdDevFromAnalyisObjtsEvaPlotTransfToStatFromAnalysisObjtsEvaRunningMeanTrendtsEvaSampleDatatsEvaTransformSeriesToStationaryMMXTrendtsEvaTransformSeriesToStationaryMultiplicativeSeasonalitytsEvaTransformSeriesToStationaryPeakTrendtsEvaTransformSeriesToStationaryTrendAndChangeptstsEvaTransformSeriesToStationaryTrendAndChangepts_ciPercentiletsEvaTransformSeriesToStationaryTrendOnlytsEvaTransformSeriesToStationaryTrendOnly_ciPercentiletsEvaTransformSeriesToStatSeasonal_ciPercentiletsEVstatisticstsGetNumberPerYeartsGetPOT
Dependencies:anytimeBHchangepointclicpp11dplyrevdfarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclelubridatemagrittrmomentsmvtnormpillarpkgconfigPOTpracmaR6RColorBrewerRcpprlangS7scalestexmextibbletidyselecttimechangetsibbleutf8vctrsviridisLitewithrxtszoo
