R: Method: Fitting the Semi-Parametric Distribution
spdfit-methods
R Documentation
Method: Fitting the Semi-Parametric Distribution
Description
The semi-parametric distribution fitting method.
Usage
spdfit(data, upper = 0.9, lower = 0.1, tailfit="GPD", type = c("mle", "pwm"),
kernelfit = c("normal", "box", "epanech", "biweight", "triweight"),
information = c("observed", "expected"), title = NULL, description = NULL, ...)
Arguments
data
An object coercible to a matrix.
upper
Upper tail cutoff for fitting the generalized pareto or other distribution.
lower
Lower tail cutoff for fitting the generalized pareto or other distribution.
tailfit
Distribution to Use for fitting the tails.
type
A character string selecting the desired estimation method, either "mle" for the maximum likelihood method or
"pwm" for the probability weighted moment method. By default, the first will be selected.
kernelfit
Type of kernel to fit to the interior of the distribution.
information
Whether tail distribution standard errors should be calculated with "observed" or "expected" information.
This only applies to the maximum likelihood method; for the probability-weighted moments method "expected" information
is used if possible.
title
A character string which allows for a project title.
description
A character string which allows for a brief description.
...
Control parameters and plot parameters optionally passed to the optimization and/or plot function.
Parameters for the optimization function are passed to components of the control argument of optim.