The use of two-component mixture models with one completely or partly known
type: Item
instance of: scholarly article
title: The use of two-component mixture models with one completely or partly known
zbMATH Open document ID: 0936.62081
author: Ekkehart Dietz
author: Dankmar Böhning
published in: Computational Statistics
publication date: 2000-03-02T00:00:00Z
review text: Procedures are given which provide maximum likelihood estimators of the unknown parameters of mixture models that have only two components. Generalized deviances based on a generalized likelihood ratio test are proposed. A simulated data set is used to show the merits of using the prior knowledge of one mixture component to improve the effect estimates and the respective inference.
Mathematics Subject Classification ID: 62J12
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62F30
zbMATH DE Number: 1409729
zbMATH Keywords: mixed generalized linear models
zbMATH Keywords: overdispersion
zbMATH Keywords: maximum likelihood estimators
zbMATH Keywords: outliers
reviewed by: M. P. Moklyachuk
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 1409729