likelihood.augmented: Calculated the augmented negative log likelihood of the GEV...

View source: R/opti.R

likelihood.augmentedR Documentation

Calculated the augmented negative log likelihood of the GEV or GP function.

Description

This function uses the likelihood function and adds the linear constraints used in fit.gev and fit.gpd to produce the augmented Lagrangian version of the GEV or GP negative log-likelihood function.

Usage

likelihood.augmented(parameters, x.in, model = c("gev", "gpd"),
  lagrangian.multiplier = rep(0, length(x.in) + 2),
  penalty.parameter = 1000)

Arguments

parameters

Numerical vector containing the location, scale, and shape parameters for the GEV or the scale and shape parameters for the GP. If NULL, likelihood.initials is used to determine them. Default = NULL

x.in

Time series of class xts.

model

String determining whether to calculate the initial parameters of the GEV ("gev") or GP ("gpd") function. Default = "gev"

lagrangian.multiplier

Lagrangian multipliers used to weight the linear contribution of the constraints. In most cases all of them are zero, since optimization of the GEV/GP likelihood usually doesn't take place inside a region of constraint violations. When supplying this parameter it has to have the same length as present number of constraints: number of points in x.in + 2. Default = 0 for all constraints.

penalty.parameter

Penalty parameter used to weight the quadratic contribution of the constraints. In the end of a typical constrained GEV or GP optimization this parameter is 1000. Default = 1000.

Details

A convenience function not used by the fitting routines.

It is only meant to work with constant parameters and no covariates.

x.in is not called "x", since the call grad( func = likelihood, x = parameters, ... ) wouldn't be possible.

Value

Numerical value of the augmented negative log likelihood.

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.gradient.augmented, likelihood.gradient, likelihood.initials, likelihood


philmu/climex documentation built on July 11, 2022, 3:23 p.m.