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商品詳細
Linear Models and the Relevant Distributions and Matrix Algebra.
・ISBN 978-0-367-57203-7 paper GB£ 47.99
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| 著者・編者 | Harville, David A., |
|---|---|
| シリーズ | Chapman & Hall/CRC Texts in Statistical Science |
| 出版社 | (Chapman & Hall/CRC, UK) |
| 出版年月 | 2020 |
| ページ数 | 538 pp. |
| 言語 | ENG |
| ニュース番号 | ＜M25-6844＞ |
解説
Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models, or a resource used (in a course on mathematical statistics) to illustrate various theoretical concepts in the context of a relatively complex setting of great practical importance.
Features:
- Provides coverage of matrix algebra that is extensive and relatively self-contained and does so in a meaningful contex
- Provides thorough coverage of the relevant statistical distributions, including spherically and elliptically symmetric distributions
- Includes extensive coverage of multiple-comparison procedures (and of simultaneous confidence intervals), including procedures for controlling the k-FWER and the FDR
- Provides thorough coverage (complete with detailed and highly accessible proofs) of results on the properties of various linear-model procedures, including those of least squares estimators and those of the F test.
- Features the use of real data sets for illustrative purposes
- Includes many exercises