GPDFit: Generalised Pareto likelihood maximisation using L-BFGS-B...

In vali2noisy/ev-trawl: Extreme Value Trawls

Description

Generalised Pareto likelihood maximisation using L-BFGS-B optimisation routine.

Usage

GPDFit(values, initial_guess, lower = c(0.1, 0.1), upper = c(20, 20))

Arguments

values	Exceedance values.
initial_guess	(at least 2-d) Vector for GPD parameters starting values.
lower	Vector of lower bounds limits for optimisation procedure. Default c(0.1, 0.1).
upper	Vector of upper bounds limits for optimisation procedure. Default c(20, 20).

Value

Parameters of Log-likelihood maximisation of GPD distribued variables (i.e. non-zero exceedances).

Examples

GPDFit(c(2.0, 0.3, 6.15, 0, 0.31), c(2.1, 1.17, 0.52, 4.17))

vali2noisy/ev-trawl documentation built on May 13, 2019, 4:09 a.m.