ML-Estimation in the Location-Scale-Shape Model of the Generalized Logistic Distribution

A three parameter (location, scale, shape) generalization of the logistic distribution is fitted to data. Local maximum likelihood estimators of the parameters are derived. Although the likelihood function is unbounded, the likelihood equations have a consistent root. ML-estimation combined with the ECM algorithm allows the distribution to be easily fitted to data.

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Year of publication:	2002
Authors:	Abberger, Klaus
Publisher:	Konstanz : University of Konstanz, Center of Finance and Econometrics (CoFE)
Subject:	Theorie \| Maximum-Likelihood-Methode \| Statistische Verteilung \| ECM algorithm \| generalized logistic distribution \| location-scale-shape model \| maximum likelihood estimation

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Series:	CoFE Discussion Paper ; 02/15
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	870059467 [GVK] hdl:10419/85186 [Handle] RePEc:zbw:cofedp:0215 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010324051