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Titlebook: Optimal Unbiased Estimation of Variance Components; James D. Malley Book 1986 Springer-Verlag Berlin Heidelberg 1986 Algebraic structure.C

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11#
發(fā)表于 2025-3-23 12:06:50 | 只看該作者
12#
發(fā)表于 2025-3-23 15:46:38 | 只看該作者
Optimal Unbiased Estimation of Variance Components978-1-4615-7554-2Series ISSN 0930-0325 Series E-ISSN 2197-7186
13#
發(fā)表于 2025-3-23 21:22:49 | 只看該作者
0930-0325 Overview: 978-0-387-96449-2978-1-4615-7554-2Series ISSN 0930-0325 Series E-ISSN 2197-7186
14#
發(fā)表于 2025-3-23 22:31:00 | 只看該作者
Lecture Notes in Statisticshttp://image.papertrans.cn/o/image/702946.jpg
15#
發(fā)表于 2025-3-24 04:52:10 | 只看該作者
https://doi.org/10.1007/978-1-4615-7554-2Algebraic structure; Calculation; Matrix; Statistica; Variance; boundary element method; estimator; form; fr
16#
發(fā)表于 2025-3-24 09:50:17 | 只看該作者
The Basic Model and The Estimation Problem,del. Then we state the essential estimation problem. Relationships among a constellation of possible estimation criteria are next studied, and finally an ordered combination of these key ideas is taken as the focus of our unbiased theory. In Chapter Ten we will look at a new combination of criteria involving non-negativity.
17#
發(fā)表于 2025-3-24 12:27:27 | 只看該作者
Basic Linear Technique,, a subject we take up in the next chapter. The notions of vec, mat., I., tensor products ?, and some relations between them are discussed. Next are the space of symmetric matrices, its natural inner product, and a useful projection lemma.
18#
發(fā)表于 2025-3-24 18:24:33 | 只看該作者
19#
發(fā)表于 2025-3-24 21:59:21 | 只看該作者
The General Solution to Optimal Unbiased Estimation,unbiased translation invariant, and optimal in the sense of then having minimum variance. It is here that we also introduce structural ideas that are taken up more completely in the following chapters.
20#
發(fā)表于 2025-3-25 00:44:56 | 只看該作者
Background from Algebra,. We have made an effort to keep the definitions to the minimum needed for an adequate description of this structure theory. Examples have been collected from the statistical literature which have a nontrivial algebraic content, but which may not have been appreciated as such by many readers.
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