In All Likelihood
Statistical Modelling and Inference Using Likelihood
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Product details:
- Publisher OUP Oxford
- Date of Publication 21 June 2001
- ISBN 9780198507659
- Binding Hardback
- No. of pages544 pages
- Size 238x161x34 mm
- Weight 944 g
- Language English
- Illustrations numerous figures 0
Categories
Short description:
This book introduces likelihood as an unifying concept in statistical modelling and inference. The complete range of concepts and applications are covered, from very simple to very complex studies. The approach is largely informal, relying on realistic examples, and presents the main results using heuristic rather than formal mathematical arguments.
MoreLong description:
Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept ot the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from a simile comparison of two accident rates, to complex studies that require generalised linear or semiparametric modelling.
The emphasis is that the likelihood is not simply a device to produce an estimate, but an important tool for modelling. The book generally takes an informal approach, where most important results are established using heuristic arguments and motivated with realistic examples. With the currently available computing power, examples are not contrived to allow a closed analytical solution, and the book can concentrate on the statistical aspects of the data modelling. In addition to classical likelihood theory, the book covers many modern topics such as generalized linear models and mixed models, non parametric smoothing, robustness, the EM algorithm and empirical likelihood.
This is a splendid book with its contents thoroughly covering all likelihood ... Statements are firm, and explanations are full and clear. This book may be used as a reference work. It is strongly recommended as an academic library volume, and individually for statistics lecturers, advanced students, and researchers.
Table of Contents:
Introduction
Elements of likelihood inference
More properties of the likelihood
Basic models and simple applications
Frequentist properties
Modelling relationships: regression models
Evidence and the likelihood principle
Score function and Fisher information
Large Sample Results
Dealing with nuisance parameters
Complex data structure
EM Algorithm
Robustness of likelihood specification
Estimating equation and quasi-likelihood
Empirical likelihood
Likelihood of random parameters
Random and mixed effects models
Nonparametric smoothing
