Restricted Maximum Likelihood (REML) Estimation of Variance Components in the Mixed Model
作者:
R.R. Corbeil,
S.R. Searle,
期刊:
Technometrics
(Taylor Available online 1976)
卷期:
Volume 18,
issue 1
页码: 31-38
ISSN:0040-1706
年代: 1976
DOI:10.1080/00401706.1976.10489397
出版商: Taylor & Francis Group
关键词: Variance Components;Mixed Model;Restricted Maximum Likelihood;Maximum Likelihood;W-transformation
数据来源: Taylor
摘要:
The maximum likelihood (ML) procedure of Hartley aud Rao [2] is modified by adapting a transformation from Pattersou and Thompson [7] which partitions the likelihood render normality into two parts, one being free of the fixed effects. Maximizing this part yields what are called restricted maximum likelihood (REML) estimators. As well as retaining the property of invariance under translation that ML estimators have, the REML estimators have the additional property of reducing to the analysis variance (ANOVA) estimators for many, if not all, cases of balanced data (equal subclass numbers).
点击下载:
PDF (731KB)
返 回