Statistical Models

A. C. Davison

Hardback ISBN 0-521-77339-3

How to order this book from Cambridge University Press.

Statistical Models was published by Cambridge University Press in June 2003.

The book is written by Anthony Davison, Professor of Statistics at the Swiss Federal Institute of Technology, Lausanne.

A file of the table of contents, Preface, Chapter 1, and the start of Chapter 2 is available here (PDF).  Here are errata.

Questions or comments regarding the book should be addressed to

Software (with apologies for the delay)

Here are the practicals, and here is the R library (tar file) and (zip file) to go with them (with thanks to Alessandra Brazzale and Diego Kuonen).  For more details about R, including how to download and install it and the many R libraries kindly written by generous souls, see this link.

Jacket Blurb

Models and likelihood are the backbone of modern statistics.  This book gives an integrated development of these topics that blends theory and practice, intended for advanced undergraduate and graduate students, researchers and practicioners. Its breadth is unrivalled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics such as likelihood and linear and generalized linear models. Each chapter contains a wide range of problems and exercises. Practicals in the S language designed to build computing and data analysis skills, and a library of data sets to accompany the book, are available over the web.

Chapter Contents

1.  Introduction
2.  Variation
3.  Uncertainty
4.  Likelihood
5.  Models
6.  Stochastic Models
7.  Estimation and Hypothesis Testing
8.  Linear Regression Models
9.  Designed Experiments
10. Nonlinear Regression Models
11. Bayesian Models
12. Conditional and Marginal Inference
Appendix: Practicals
Name Index
Example Index

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