| spdfit-methods {spd} | 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 |
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. |
Value
Returns an object of class SPD.
Examples
## Not run:
library(MASS)
x<-SP500/100
fit<-spdfit(x)
show(fit)
#plot(fit,which="all")
## End(Not run)