tsEvaPlotGPDImageScFromAnalysisObj {RtsEva} | R Documentation |
tsEvaPlotGPDImageScFromAnalysisObj
Description
tsEvaPlotGPDImageScFromAnalysisObj
is a function that plots the GPD
(Generalized Pareto Distribution) time-varying distribution through time as
and show the evolution of exceedance probabilities.
Usage
tsEvaPlotGPDImageScFromAnalysisObj(
Y,
nonStationaryEvaParams,
stationaryTransformData,
trans,
...
)
Arguments
Y |
The input data. |
nonStationaryEvaParams |
A list containing non-stationary evaluation parameters. |
stationaryTransformData |
A data frame containing stationary transform data. |
trans |
The transformation method to be applied to the data. |
... |
Additional arguments to be passed to the |
Details
This function takes the input data Y
, non-stationary evaluation parameters nonStationaryEvaParams
,
stationary transform data stationaryTransformData
, transformation method trans
, and additional arguments ...
.
It then updates the arguments with the passed-in values, calculates the time stamps, and performs necessary transformations.
Finally, it plots the GPD image score using the tsEvaPlotGPDImageSc
function and returns the plot object.
Value
The plot object.
See Also
Examples
# Example usage of TsEvaNs function
timeAndSeries <- ArdecheStMartin
#go from six-hourly values to daily max
timeAndSeries <- max_daily_value(timeAndSeries)
#keep only the 20 last years
yrs <- as.integer(format(timeAndSeries$date, "%Y"))
tokeep <- which(yrs>=2000)
timeAndSeries <- timeAndSeries[tokeep,]
timeWindow <- 5*365 # 5 years
TSEVA_data <- TsEvaNs(timeAndSeries, timeWindow,
transfType = 'trendPeaks',tail = 'high')
nonStationaryEvaParams <- TSEVA_data[[1]]
stationaryTransformData <- TSEVA_data[[2]]
trans='ori'
ExRange= c(min(nonStationaryEvaParams$potObj$parameters$peaks),
max(nonStationaryEvaParams$potObj$parameters$peaks))
Y <- c(seq(min(ExRange),max(ExRange),length.out=700))
result = tsEvaPlotGEVImageScFromAnalysisObj(Y, nonStationaryEvaParams,
stationaryTransformData, trans)
result