likelihood.gradient: Gradient of the likelihood of the GEV and GP distribution

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

Gradient of the likelihood of the GEV and GP distribution

Description

Calculates the gradient of the negative log likelihood of the GEV or GP function.

Usage

likelihood.gradient(parameters, x.in, model = c("gev", "gpd"))

Arguments

parameters	Numerical vector containing the location, scale, and shape parameters for the GEV model or the scale and shape parameters for the GP one.
x.in	Time series of class xts or numerical vector containing the extreme events.
model	String determining whether to calculate the initial parameters of the GEV ("gev") or GP ("gpd") function. Default = "gev".

Value

Numerical vector containing the derivative of the negative log-likelihood in (location, scale, shape for GEV) or (scale, shape for GP) direction.

Author(s)

Philipp Mueller

See Also

Other optimization: fit.gev.default, fit.gev.list, fit.gev.xts, fit.gev, fit.gpd.default, fit.gpd.list, fit.gpd.xts, fit.gpd, likelihood.augmented, likelihood.gradient.augmented, likelihood.initials, likelihood

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