G. A. Young

Essentials of Statistical Inference (eBook, PDF)

• Format: PDF

Produktbeschreibung

Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between them. Computational ideas are explained, as well as basic mathematical theory. Written in a lucid and informal style, this concise text provides both basic material on the main approaches to inference, as well as more advanced material on developments in statistical theory, including: material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 25. Juli 2005
• Englisch
• ISBN-13: 9780511124020
• Artikelnr.: 38187938

Autorenporträt

G. A. Young is Professor of Statistics at Imperial College London.

Inhaltsangabe

1. Introduction
2. Decision theory
3. Bayesian methods
4. Hypothesis testing
5. Special models
6. Sufficiency and completeness
7. Two-sided tests and conditional inference
8. Likelihood theory
9. Higher-order theory
10. Predictive inference
11. Bootstrap methods.

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1. Introduction; 2. Decision theory; 3. Bayesian methods; 4. Hypothesis testing; 5. Special models; 6. Sufficiency and completeness; 7. Two-sided tests and conditional inference; 8. Likelihood theory; 9. Higher-order theory; 10. Predictive inference; 11. Bootstrap methods.

Rezensionen

'This is a delightful book! It gives a well-written exposure to inference issues in statistics, very suitable for a first-year graduate course ... The authors present the material in a very good pedagogical manner. The examples are excellent, and the exercises are very instructive ... very much up to date and includes recent developments in the field.' MAA Reviews