{ "item_title" : "Optimal Unbiased Estimation of Variance Components", "item_author" : [" James D. Malley "], "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 Rao1971a, 1971b] and his MINQUE estimators, and related to these but not originally derived from them, the results of Seely1971] obtained as part of his introduction of the no ion of quad- ratic subspace into the literature of variance component estimation. These two approaches were ultimately shown to be intimately related by Pukelsheim1976], who used a linear model for the com- ponents given by Mitra1970], and in so doing, provided a mathemati- cal framework for estimation which permitted the immediate applica- tion 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 enor- mous linear model for the components can be displayed as the starting point for many of the popular variance component estimation tech- niques, thereby unifying the subject in addition to generating answers.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/0/38/796/449/0387964495_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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