Package: RtsEva 1.0.0

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:Alois Tilloy [aut, cre]

RtsEva_1.0.0.tar.gz
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RtsEva.pdf |RtsEva.html
RtsEva/json (API)
NEWS

# Install 'RtsEva' in R:
install.packages('RtsEva', repos = c('https://alowis.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

On CRAN:

extreme-value-statisticsnon-stationary-environment

51 exports 4 stars 1.83 score 48 dependencies 4 scripts 523 downloads

Last updated 8 days agofrom:3b1ee8123c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-winOKSep 10 2024
R-4.5-linuxOKSep 10 2024
R-4.4-winOKSep 10 2024
R-4.4-macOKSep 10 2024
R-4.3-winOKSep 10 2024
R-4.3-macOKSep 10 2024

Exports:check_timeseriescomputeAnnualMaximacomputeMonthlyMaximadeclustpeaksempdisempdislfindMaxinitPercentilesmax_daily_valuetsEasyParseNamedArgstsEstimateAverageSeasonalitytsEvaChangeptstsEvaComputeReturnLevelsGEVtsEvaComputeReturnLevelsGEVFromAnalysisObjtsEvaComputeReturnLevelsGPDtsEvaComputeReturnLevelsGPDFromAnalysisObjtsEvaComputeReturnPeriodsGEVtsEvaComputeReturnPeriodsGPDtsEvaComputeRLsGEVGPDtsEvaComputeTimeRPtsEvaDetrendTimeSeriestsEvaFillSeriestsEvaFindTrendThresholdtsEvaNanRunnigBlowThtsEvaNanRunningMeantsEvaNanRunningPercentilestsEvaNanRunningStatisticstsEvaNanRunningVarianceTsEvaNstsEvaPlotAllRLevelsGEVtsEvaPlotAllRLevelsGPDtsEvaPlotGEVImageScFromAnalysisObjtsEvaPlotGPDImageScFromAnalysisObjtsEvaPlotReturnLevelsGEVtsEvaPlotReturnLevelsGEVFromAnalysisObjtsEvaPlotReturnLevelsGPDtsEvaPlotReturnLevelsGPDFromAnalysisObjtsEvaPlotSeriesTrendStdDevFromAnalyisObjtsEvaPlotTransfToStatFromAnalysisObjtsEvaRunningMeanTrendtsEvaSampleDatatsEvaTransformSeriesToStationaryMultiplicativeSeasonalitytsEvaTransformSeriesToStationaryPeakTrendtsEvaTransformSeriesToStationaryTrendAndChangeptstsEvaTransformSeriesToStationaryTrendAndChangepts_ciPercentiletsEvaTransformSeriesToStationaryTrendOnlytsEvaTransformSeriesToStationaryTrendOnly_ciPercentiletsEvaTransformSeriesToStatSeasonal_ciPercentiletsEVstatisticstsGetNumberPerYeartsGetPOT

Dependencies:anytimeBHchangepointclicolorspacecpp11dplyrellipsisevdfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclelubridatemagrittrMASSMatrixmgcvmomentsmunsellmvtnormnlmepillarpkgconfigPOTpracmaR6RColorBrewerRcpprlangscalestexmextibbletidyselecttimechangetsibbleutf8vctrsviridisLitewithrxtszoo

Transformed-stationary EVA workflow example

Rendered fromgeneral-demo.Rmdusingknitr::rmarkdownon Sep 10 2024.

Last update: 2024-06-06
Started: 2024-06-06

Readme and manuals

Help Manual

Help pageTopics
Simulated river discharge of the Ardeche river at Saint Martin d'ArdecheArdecheStMartin
Check if all years in a time series are presentcheck_timeseries
computeAnnualMaximacomputeAnnualMaxima
computeMonthlyMaximacomputeMonthlyMaxima
Simulated river discharge of the Danube river at ViennaDanubeVienna
declustpeaksdeclustpeaks
Simulated river discharge of the Ebro river at ZaragozaEbroZaragoza
empdis: Empirical Distribution Functionempdis
Empirical Distribution Functionempdisl
findMaxfindMax
Initialize PercentilesinitPercentiles
Max Daily Value Functionmax_daily_value
Simulated river discharge of the Rhone river at LyonRhoneLyon
Parse named arguments and assign values to a predefined argument structure.tsEasyParseNamedArgs
Estimate Average SeasonalitytsEstimateAverageSeasonality
Change point detection in time seriestsEvaChangepts
tsEvaComputeReturnLevelsGEVtsEvaComputeReturnLevelsGEV
tsEvaComputeReturnLevelsGEVFromAnalysisObjtsEvaComputeReturnLevelsGEVFromAnalysisObj
tsEvaComputeReturnLevelsGPDtsEvaComputeReturnLevelsGPD
tsEvaComputeReturnLevelsGPDFromAnalysisObjtsEvaComputeReturnLevelsGPDFromAnalysisObj
tsEvaComputeReturnPeriodsGEVtsEvaComputeReturnPeriodsGEV
tsEvaComputeReturnPeriodsGPDtsEvaComputeReturnPeriodsGPD
tsEvaComputeRLsGEVGPDtsEvaComputeRLsGEVGPD
tsEvaComputeTimeRPtsEvaComputeTimeRP
Detrend a Time SeriestsEvaDetrendTimeSeries
Fill missing values in a time series using a moving average approach.tsEvaFillSeries
Find Trend ThresholdtsEvaFindTrendThreshold
Calculate the return period of low flow based on a threshold and window sizetsEvaNanRunnigBlowTh
Calculate the running mean of a time series with NaN handlingtsEvaNanRunningMean
tsEvaNanRunningPercentilestsEvaNanRunningPercentiles
tsEvaNanRunningStatisticstsEvaNanRunningStatistics
Calculate the running variance of a time series with NaN handlingtsEvaNanRunningVariance
TsEvaNs FunctionTsEvaNs
tsEvaPlotAllRLevelsGEVtsEvaPlotAllRLevelsGEV
tsEvaPlotAllRLevelsGPDtsEvaPlotAllRLevelsGPD
tsEvaPlotGEVImageSctsEvaPlotGEVImageSc
tsEvaPlotGEVImageScFromAnalysisObjtsEvaPlotGEVImageScFromAnalysisObj
tsEvaPlotGPDImageSctsEvaPlotGPDImageSc
tsEvaPlotGPDImageScFromAnalysisObjtsEvaPlotGPDImageScFromAnalysisObj
tsEvaPlotReturnLevelsGEVtsEvaPlotReturnLevelsGEV
tsEvaPlotReturnLevelsGEVFromAnalysisObjtsEvaPlotReturnLevelsGEVFromAnalysisObj
tsEvaPlotReturnLevelsGPDtsEvaPlotReturnLevelsGPD
tsEvaPlotReturnLevelsGPDFromAnalysisObjtsEvaPlotReturnLevelsGPDFromAnalysisObj
tsEvaPlotSeriesTrendStdDevFromAnalyisObjtsEvaPlotSeriesTrendStdDevFromAnalyisObj
tsEvaPlotTransfToStattsEvaPlotTransfToStat
tsEvaPlotTransfToStatFromAnalysisObjtsEvaPlotTransfToStatFromAnalysisObj
Calculate the running mean trend of a time seriestsEvaRunningMeanTrend
tsEvaSampleData FunctiontsEvaSampleData
tsEvaTransformSeriesToStationaryMultiplicativeSeasonalitytsEvaTransformSeriesToStationaryMultiplicativeSeasonality
tsEvaTransformSeriesToStationaryPeakTrendtsEvaTransformSeriesToStationaryPeakTrend
Transform Time Series to Stationary Trend and Change PointstsEvaTransformSeriesToStationaryTrendAndChangepts
Transform Time Series to Stationary Trend and Change Points with Confidence IntervalstsEvaTransformSeriesToStationaryTrendAndChangepts_ciPercentile
tsEvaTransformSeriesToStationaryTrendOnlytsEvaTransformSeriesToStationaryTrendOnly
tsEvaTransformSeriesToStationaryTrendOnly_ciPercentiletsEvaTransformSeriesToStationaryTrendOnly_ciPercentile
tsEvaTransformSeriesToStatSeasonal_ciPercentiletsEvaTransformSeriesToStatSeasonal_ciPercentile
tsEVstatisticstsEVstatistics
tsGetNumberPerYeartsGetNumberPerYear
tsGetPOT FunctiontsGetPOT