Essentials of Statistical Inference

G.A. Young, R. L. Smith - Collection Cambridge series in statistical and probabilistic mathematics

236 pages, parution le 07/12/2005

Ajouter à une liste

Indisponible

Résumé

This engaging textbook presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers in a concise treatment both basic mathematical theory and more advanced material, including such contemporary topics as Bayesian computation, 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. Some prior knowledge of probability is assumed, while some previous knowledge of the objectives and main approaches to statistical inference would be helpful but is not essential.

First text to synthesise basic mathematical theory with material on such modern computational topics as MCMC and bootstrap
Covers main approaches to statistical inference - Bayesian, frequentist, Fisherian - with emphasis on the contrasts between them
Written in an engaging style that emphasises concepts rather than dry mathematical detail, while maintaining appropriate levels of rigour

L'auteur - G.A. Young

G. A. Young : Imperial College London

L'auteur - R. L. Smith

R. L. Smith : University of North Carolina, Chapel Hill

Sommaire

Introduction
Decision theory
Bayesian methods
Hypothesis testing
Special models
Sufficiency and completeness
Two-sided tests and conditional inference
Likelihood theory
Higher-order theory
Predictive inference
Bootstrap methods
References

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	G.A. Young, R. L. Smith
Collection	Cambridge series in statistical and probabilistic mathematics
Parution	07/12/2005
Nb. de pages	236
Format	18 x 26
Couverture	Relié
Poids	590g
Intérieur	Noir et Blanc
EAN13	9780521839716
ISBN13	978-0-521-83971-6