texmex (version 2.1)

texmexFamily: Create families of distributions

Description

Create families of distributions for use with extreme value modelling.

Usage

texmexFamily(name, log.lik, param, info = NULL, start = NULL, resid =
NULL, rl, delta, endpoint, density, rng, prob, quant)
"print"(x, ...)
"summary"(object, ...)

Arguments

name

The name of the distribution.

log.lik

The distribution's log-likelihood function.

param

The names of the parameters in the model.

info

Function to compute the information matrix. If not provided, the modelling functions will work with a numerical approximation.

start

Function to compute starting parameters for the model. If not provided, the modelling functions will try to guess.

resid

Function to compute residuals for the model.

rl

Function to compute return levels.

delta

Function to compute adjustments for covariance for return levels.

endpoint

Function to compute the upper or lower endpoint of the fitted distribution.

density

Function to compute the density.

rng

Function for random number generation.

prob

Function to compute cumulative probabilities.

quant

Function to compute quantiles.

...

Additional arguments to the print and summary methods.

x, object

An object of class 'texmexFamily'.

Value

A object of class "texmexFamily", which is essentially a list containing the input arguments. If info, start, resid are not provided, they default to NULL.

Details

The density, rng, prob and quant functions can be simple wrappers for the usual d, r, p and q functions. They should take a matrix with number of columns equal to the number of parameters, and a fitted model object even if the model object is not used by the function.

Examples of "texmexFamily" objects are gpd and gev. Take a look at those objects to see how the functions should be constructed.

The functions are used by the modelling functions to create diagnostic plots, predictions, etc..

See Also

evm