UKFE (version 0.4.0)

GenParetoPars: Generalised Pareto distribution parameter estimates

Description

Estimated parameters from a sample (with Lmoments or maximum likelihood estimation) or from L1 (first L-moment), Lcv (linear coefficient of variation), and LSkew (linear skewness)

Usage

GenParetoPars(x = NULL, mle = FALSE, L1, LCV, LSKEW)

Value

Parameter estimates (location, scale, shape)

Arguments

x

numeric vector. The sample

mle

logical argument with a default of FALSE. If FALSE the parameters are estimated with Lmoments, if TRUE the parameters are estimated by maximum likelihood estimation

L1

first Lmoment

LCV

linear coefficient of variation

LSKEW

linear skewness

Author

Anthony Hammond

Details

The L-moment estimated parameters are by the method detailed in 'Hosking J. Wallis J. 1997 Regional Frequency Analysis: An Approach Based on L-moments. Cambridge University Press, New York'

Examples

#Get a peaks over threshold sample and estimate the parameters using Lmoments
ThamesPOT <- ThamesPOT <- POTextract(ThamesPQ[,c(1,3)], thresh = 0.90)
GenParetoPars(ThamesPOT$peak)
#Estimate parameters using MLE
GenParetoPars(ThamesPOT$peak, mle = TRUE)
#calculate Lmoments and estimate the parmeters with L1, Lcv and Lskew
LMoments(ThamesPOT$peak)
#store linear moments in an object
LPars <- as.numeric(LMoments(ThamesPOT$peak))[c(1,5,6)]
GenParetoPars(L1 = LPars[1], LCV = LPars[2], LSKEW = LPars[3])