Statistical inference in linear models
著者
書誌事項
Statistical inference in linear models
（Wiley series in probability and mathematical statistics, . Applied probability and statistics . Statistical methods of model building ; v. 1）
John Wiley, c1986
- タイトル別名
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Statistische Inferenz für lineare Parameter
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注記
Translation of: Statistische Methoden der Modellbildung / K.M.S. Humak. Bd. 1. Statistische Inferenz für lineare Parameter. Berlin : Akademie-Verlag, 1977
Includes index
"The author's name (K.M.S. Humak) in the German edition is a pseudonym for Kollektiv Mathematische Statistik: Humboldt Universität zu Berlin and Akademie der Wissenschaften der DDR"--Translators' pref. verso
内容説明・目次
内容説明
This is a comprehensive account of the theory of the linear model, and covers a wide range of statistical methods. Topics covered include estimation, testing, confidence regions, Bayesian methods and optimal design. These are all supported by practical examples and results; a concise description of these results is included in the appendices. Material relating to linear models is discussed in the main text, but results from related fields such as linear algebra, analysis, and probability theory are included in the appendices. The information includes advances in the UK and US, as well as the USSR and German Democratic Republic.
目次
- Statistical problems in modelling causal relationships
- estimating linear parameters
- estimating linear parameters using additional information
- admissibility and improvements of the generalized least squares estimator
- testing linear hypotheses
- confidence regions for linear parameters and regression functions
- Bayesian methods and structural inference
- experimental design methods.
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