Essentials of Statistical Inference

Erscheinungsjahr 2014
ISBN: 978-0-521-54866-3
Verlag: Cambridge University Press

Buch, Englisch, Band 16, 236 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 415 g

Reihe: Cambridge Series in Statistical and Probabilistic Mathematics

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. Contemporary 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 modern developments in statistical theory, including: contemporary 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.

Autoren/Hrsg.

Young, G. A.

Smith, R. L.

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

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.

Über Autor(innen)

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

Smith, R. L.
R. L. Smith is Mark L. Reed Distinguished Professor of Statistics at the University of North Carolina, Chapel Hill.