Estimate and compute log-likelihood of the standardised Generalised Error Distribution (GED)

Description

gedestp and gedlogl are auxiliary functions called by gets.mean and gets.vol.

The gedestp function estimates the shape parameter of a standardised (zero mean, unit variance) GED. The estimation method is based on an index of kurtosis approach, and the code is based on the estimatep function from the normalp package by Angelo M. Mineo.

The gedlogl function computes the log-likelihood of a standardised GED with shape parameter p.

Usage

gedestp(x, method = c("inverse", "direct"))
gedlogl(z, p = 2)

Arguments

Value

numeric, either an estimate of the shape parameter or the log-likelihood

Author(s)

Genaro Sucarrat (http://www.sucarrat.net/)

References

Mineo, A.M. (1994): 'Un nuovo metodo di stima di p per una corretta valutazione dei parametri diintensita e di scala di una curva normale di ordine p', Atti della XXXVII Riunione Scientifica della Societa Italiana di Statistica, San Remo, Vol. 2, pp. 147-154

See Also

gets.mean, gets.vol

Examples

#estimate p of a standard normal:
set.seed(123)
x <- rnorm(200)
gedestp(x)

#log-likelihood of the standard normal series:
gedlogl(x, p=2)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(AutoSEARCH)
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: lgarch
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AutoSEARCH/gedestp.Rd_%03d_medium.png", width=480, height=480)
> ### Name: gedestp
> ### Title: Estimate and compute log-likelihood of the standardised
> ###   Generalised Error Distribution (GED)
> ### Aliases: gedestp gedlogl
> ### Keywords: Statistical Models Time Series Financial Econometrics
> 
> ### ** Examples
> 
> #estimate p of a standard normal:
> set.seed(123)
> x <- rnorm(200)
> gedestp(x)
[1] 1.8415
> 
> #log-likelihood of the standard normal series:
> gedlogl(x, p=2)
[1] -272.3053
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>