RtsEva (version 1.1.0)

tsEvaPlotReturnLevelsGPDFromAnalysisObj: tsEvaPlotReturnLevelsGPDFromAnalysisObj

Description

tsEvaPlotReturnLevelsGPDFromAnalysisObj is a function that plots the return levels for a Generalized Pareto Distribution (GPD) using the parameters obtained from an analysis object. It considers non-stationarity by considering time-varying parameters and their associated standard errors.

Usage

tsEvaPlotReturnLevelsGPDFromAnalysisObj(
  nonStationaryEvaParams,
  stationaryTransformData,
  timeIndex,
  trans,
  ...
)

Value

Plot 1

RLtstep: return level curve with confidence interval for the selected timeIndex

Plot 2

beam: beam of return level curve for all with highlited curve for selected timeIndex

Arguments

nonStationaryEvaParams

The non-stationary parameters obtained from the analysis object.

stationaryTransformData

The stationary transformed data obtained from the analysis object.

timeIndex

The index at which the time-varying analysis should be estimated.

trans

The transformation used to fit the EVD. Can be "ori" for no transformation or "rev" for reverse transformation.

...

Additional arguments to be passed to the function.

References

Mentaschi, L., Vousdoukas, M., Voukouvalas, E., Sartini, L., Feyen, L., Besio, G., and Alfieri, L. (2016). The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis. Hydrology and Earth System Sciences, 20, 3527-3547. doi:10.5194/hess-20-3527-2016.

See Also

tsEvaPlotReturnLevelsGPD() and tsEvaPlotAllRLevelsGPD()

Examples

 # Example usage of TsEvaNs function
timeAndSeries <- ArdecheStMartin
#go from six-hourly values to daily max
timeAndSeries <- max_daily_value(timeAndSeries)
#keep only the 30 last years
yrs <- as.integer(format(timeAndSeries$date, "%Y"))
tokeep <- which(yrs>=1990)
timeAndSeries <- timeAndSeries[tokeep,]
timeWindow <- 10*365 # 10 years
TSEVA_data <- TsEvaNs(timeAndSeries, timeWindow,
transfType = 'trendPeaks',tail = 'high')
nonStationaryEvaParams <- TSEVA_data[[1]]
stationaryTransformData <- TSEVA_data[[2]]
timeIndex=2
trans='ori'
result = tsEvaPlotReturnLevelsGPDFromAnalysisObj(nonStationaryEvaParams, stationaryTransformData,
timeIndex, trans)
result