In All Likelihood

Statistical Modelling and Inference Using Likelihood

Yudi Pawitan

528 pages, parution le 18/12/2001

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Résumé

Presents concepts that are essential for understanding the current statistical methodology.
Informal approach makes concepts more accessible.
Realistic examples are provided to motivate the concepts.
Programs and datasets are available to reproduce the examples within the book.

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.

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

L'auteur - Yudi Pawitan

Yudi Pawitan: Karolinska Institute, Stockholm, Sweden

Caractéristiques techniques

	PAPIER
Éditeur(s)	Oxford University Press
Auteur(s)	Yudi Pawitan
Parution	18/12/2001
Nb. de pages	528
Format	16 x 24
Couverture	Relié
Poids	872g
Intérieur	Noir et Blanc
EAN13	9780198507659
ISBN13	978-0-19-850765-9