tsEvaPlotReturnLevelsGPDFromAnalysisObj {RtsEva} | R Documentation |
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,
...
)
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. |
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
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