return.level.numeric: Calculation of the return levels.

In theGreatWhiteShark/climex: Estimating Extreme Events in Climatic Time Series (using Data of the DWD)

Calculation of the return levels.

Description

Calculate arbitrary return levels and their error estimates for generalized extreme value (GEV) and generalized Pareto (GP) distributions.

Usage

## S3 method for class 'numeric'
return.level(x, return.period = 100,
  error.estimation = c("none", "MC", "MLE", "bootstrap"),
  model = c("gev", "gpd"), monte.carlo.sample.size = 100,
  bootstrap.sample.size = 100, threshold = NULL, total.length = NULL,
  thresholded.time.series = NULL, extreme.type = c("max", "min"),
  silent = FALSE, mc.cores = NULL)

Arguments

x	Of class numeric.
return.period	Numeric vector of the return periods in years. Default = 100.
error.estimation	The estimation of the fitting error is only for input argument of the class climex.fit.gev or climex.fit.gpd. Else the correct scaling of the can not be assured.
model	String determining whether to calculate the initial parameters of the GEV ("gev") or GP ("gpd") function. Default = "gev"
monte.carlo.sample.size	Number of samples used to obtain the Monte Carlo estimate of the standard error of the fitting. Default = 100.
bootstrap.sample.size	Number of samples with replacements to drawn from the original series x in order to determine the standard errors for the GEV/GP parameters and return levels. Default = 100.
threshold	Optional threshold for the GP model. If present it will be added to the return level to produce a value which fits to underlying time series. Default = NULL.
total.length	Total number of observations in the time series the exceedance were obtained from (before! applying the threshold). This argument is needed to calculate the standard error of the return level via the delta method of the MLE in the GP model. Default = NULL.
thresholded.time.series	Time series used with fit.gpd on which already a threshold (the one supplied here as well) was applied. Necessary to transform the return level for numerical input and the GP model from m-th observation return level to annual return level. If omitted the return level will be per observation. Default = NULL.
extreme.type	String indicating whether to calculate the quantiles at the right ("max") or left ("min") side of the PDF of the series. Default = "max".
silent	Throws an warning whenever the "gpd" model is used and the thresholded.time.series is not supplied. Since this can be annoying one can also disable it. Default = FALSE.
mc.cores	A numerical input specifying the number of cores to use for the multi core application of the function (see detectCores). This functionality is only available if the input is a list of different objects. If NULL, the function will be calculated classically with only one core. Default = NULL.

Details

Uses the rlevd function at its core (a port from the extRemes package) but is also capable of calculating numerous return levels at once, and also calculates the errors of the return levels. For the errors the ML fit is using the option hessian=TRUE (if not done already) or uses a Monte Carlo based approach. If no fitting object is provided, no errors will be calculated.

Value

A list containing the estimates "return.level" and their standard errors "error" if the input was a fitting object or a numerical input.

See Also

Other extremes: block.list, block.xts, block, decluster.list, decluster.xts, decluster, extremal.index, gev.density, gpd.density, qevd, return.level.climex.fit.gev, return.level.climex.fit.gpd, return.level.list, return.level, revd, rlevd, threshold.list, threshold.xts, threshold, upper.limit.climex.fit.gev, upper.limit.climex.fit.gpd, upper.limit.list, upper.limit.numeric, upper.limit

Examples

fit.results <- fit.gev( block( anomalies( temp.potsdam ) ) )
return.level( fit.results, return.period = c( 10, 50, 100 ),
              error.estimation = "MLE" )

theGreatWhiteShark/climex documentation built on July 13, 2022, 9:11 a.m.