tsEvaPlotGPDImageScFromAnalysisObj {RtsEva} | R Documentation |
tsEvaPlotGPDImageScFromAnalysisObj
is a function that plots the GPD
(Generalized Pareto Distribution) time-varying distribution through time as
and show the evolution of exceedance probabilities.
tsEvaPlotGPDImageScFromAnalysisObj(
Y,
nonStationaryEvaParams,
stationaryTransformData,
trans,
...
)
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 |
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.
The plot object.
# 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