Optimal Unbiased Estimation of Variance Components:
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Bibliographic Details
Main Author: Malley, James D. (Author)
Format: Electronic eBook
Language:English
Published: New York, NY Springer New York 1986
Series:Lecture Notes in Statistics 39
Subjects:
Online Access:Volltext
Item Description:The clearest way into the Universe is through a forest wilderness. John Muir As recently as 1970 the problem of obtaining optimal estimates for variance components in a mixed linear model with unbalanced data was considered a miasma of competing, generally weakly motivated estimators, with few firm guidelines and many simple, compelling but Unanswered questions. Then in 1971 two significant beachheads were secured: the results of Rao [1971a, 1971b] and his MINQUE estimators, and related to these but not originally derived from them, the results of Seely [1971] obtained as part of his introduction of the notion of quadratic subspace into the literature of variance component estimation. These two approaches were ultimately shown to be intimately related by Pukelsheim [1976], who used a linear model for the components given by Mitra [1970], and in so doing, provided a mathematical framework for estimation which permitted the immediate application of many of the familiar Gauss-Markov results, methods which had earlier been so successful in the estimation of the parameters in a linear model with only fixed effects. Moreover, this usually enormous linear model for the components can be displayed as the starting point for many of the popular variance component estimation techniques, thereby unifying the subject in addition to generating answers
Physical Description:1 Online-Ressource (X, 146 p.) 1 illus
ISBN:9781461575542
9780387964492
ISSN:0930-0325
DOI:10.1007/978-1-4615-7554-2

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