Estimation of variance components in an unbalanced two-way mixed model under heteroskedasticity
type: Item
instance of: scholarly article
title: Estimation of variance components in an unbalanced two-way mixed model under heteroskedasticity
zbMATH Open document ID: 0665.62070
DOI: 10.1016/0378-3758(89)90047-5
author: Kalyan Das
published in: Journal of Statistical Planning and Inference
publication date: 1989-01-01T00:00:00Z
review text: In an unbalanced two-way mixed model with random column effects where the error variance changes from cell to cell, the problem of estimation of variance components due to column effects and interactions is considered. Since with the increase in the size of the experiment, the number of error variances increases indefinitely, the problem of finding efficient estimates of the two variance components looks intractable. However, by grouping the cells according to cell frequencies, it is possible to construct an estimate with good asymptotic properties. A comparison with the members of a class of estimates arising from intuitive considerations, is also made.
Mathematics Subject Classification ID: 62J10
Mathematics Subject Classification ID: 62E20
zbMATH DE Number: 4088761
zbMATH Keywords: heteroskedasticity
zbMATH Keywords: unbalanced two-way mixed model
zbMATH Keywords: random column effects
zbMATH Keywords: estimation of variance components
zbMATH Keywords: interactions
zbMATH Keywords: efficient estimates
zbMATH Keywords: grouping
zbMATH Keywords: cell frequencies
zbMATH Keywords: asymptotic properties
MaRDI profile type: Publication
full work available at URL: 0378-3758(89)90047-5
OpenAlex ID: W2006108259
cites work: Q5653456
cites work: Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
cites work: Consistent Estimates Based on Partially Consistent Observations
description: scientific article; zbMATH DE number 4088761