Maximum likelihood estimation of random effects models
type: Item
instance of: scholarly article
title: Maximum likelihood estimation of random effects models
zbMATH Open document ID: 0628.62109
DOI: 10.1016/0304-4076(87)90010-8
author: Trevor S. Breusch
published in: Journal of Econometrics
publication date: 1987-01-01T00:00:00Z
review text: Iterated GLS has a remarkable property when applied to the random effects model in its usual parameterization. The values for the parameter that measures relative variance, obtained through successive iterations, form a monotonic sequence. This property provides convenient checks for multiple maxima of the likelihood function and for existence of a local maximum that satisfies the non-negativity condition.
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 62J10
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62H12
zbMATH DE Number: 4022449
zbMATH Keywords: maximum likelihood estimation
zbMATH Keywords: generalized least squares
zbMATH Keywords: Iterated GLS
zbMATH Keywords: random effects model
zbMATH Keywords: multiple maxima
zbMATH Keywords: likelihood function
zbMATH Keywords: existence of a local maximum
zbMATH Keywords: non-negativity condition
MaRDI profile type: Publication
full work available at URL: 0304-4076(87)90010-8
OpenAlex ID: W2005455377
cites work: Panel Data and Unobservable Individual Effects
cites work: A General Procedure for Obtaining Maximum Likelihood Estimates in Generalized Regression Models
description: scientific article; zbMATH DE number 4022449