ThrSelection: Threshold selection

In circularEV: Extreme Value Analysis for Circular Data

Threshold selection

Description

This function selects a moving threshold for circular data using an automatic procedure for selecting the local number of exceedances

Usage

ThrSelection(
  Data,
  drc,
  h = 30,
  b = 0.35,
  thetaGrid,
  EVIestimator = "ML",
  useKernel = TRUE,
  concent = 10,
  bw = 30,
  numCores = 2
)

Arguments

Data	Response variable
drc	Directional covariate
h	Bandwidth value
b	Parameter used in the automatic procedure for selection of local number of exceedances
thetaGrid	Grid values at which the estimation is performed
EVIestimator	It can be either "ML" or "Mom"
useKernel	Logical. If TRUE (default), use kernel to assign weights depending on the directional distance.
concent	Concentration parameter value for von Mises kernel
bw	Bandwidth parameter value for smoothing the sample path of the selected threshold
numCores	Number of CPU cores to be used

Details

See Konzen, E., Neves, C., and Jonathan, P. (2021). Modeling nonstationary extremes of storm severity: Comparing parametric and semiparametric inference. Environmetrics, 32(4), e2667.

Value

List containing the selected threshold and selected number of local exceedances at each direction in the grid.

See Also

PlotData and PolarPlotData to see how the threshold can be visualised.

Examples

data(HsSP)
data(drc)
timeRange <- 54.5

idx <- order(drc)
drc <- drc[idx]
Data <- HsSP[idx]
set.seed(1234)
Data <- Data + runif(length(Data), -1e-4, 1e-4)

thetaVec <- 1:360



thrResultMom <- ThrSelection(Data=Data, drc=drc, h=60, b=0.35, thetaGrid=thetaVec,
                             EVIestimator="Mom", useKernel=T, concent=10, bw=30,
                             numCores=2)$thr
thrResultML <- ThrSelection(Data=Data, drc=drc, h=60, b=0.35, thetaGrid=thetaVec,
                            EVIestimator="ML", useKernel=T, concent=10, bw=30,
                            numCores=2)$thr



## See also examples in vignettes:
# vignette("localMethods", package = "circularEV")
# vignette("splineML", package = "circularEV")

circularEV documentation built on May 13, 2022, 5:08 p.m.