Millar Maximum Likelihood Estimation and Inference

With Examples in R, SAS and ADMB
1. Auflage 2011
ISBN: 978-1-119-97771-1
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 384 Seiten, E-Book

Reihe: Statistics in Practice

This book takes a fresh look at the popular and well-establishedmethod of maximum likelihood for statistical estimation andinference. It begins with an intuitive introduction to the conceptsand background of likelihood, and moves through to the latestdevelopments in maximum likelihood methodology, including generallatent variable models and new material for the practicalimplementation of integrated likelihood using the free ADMBsoftware. Fundamental issues of statistical inference are alsoexamined, with a presentation of some of the philosophical debatesunderlying the choice of statistical paradigm.
Key features:
* Provides an accessible introduction to pragmatic maximumlikelihood modelling.
* Covers more advanced topics, including general forms of latentvariable models (including non-linear and non-normal mixed-effectsand state-space models) and the use of maximum likelihood variants,such as estimating equations, conditional likelihood, restrictedlikelihood and integrated likelihood.
* Adopts a practical approach, with a focus on providing therelevant tools required by researchers and practitioners whocollect and analyze real data.
* Presents numerous examples and case studies across a wide rangeof applications including medicine, biology and ecology.
* Features applications from a range of disciplines, withimplementation in R, SAS and/or ADMB.
* Provides all program code and software extensions on asupporting website.
* Confines supporting theory to the final chapters to maintain areadable and pragmatic focus of the preceding chapters.
This book is not just an accessible and practical text aboutmaximum likelihood, it is a comprehensive guide to modern maximumlikelihood estimation and inference. It will be of interest toreaders of all levels, from novice to expert. It will be of greatbenefit to researchers, and to students of statistics from seniorundergraduate to graduate level. For use as a course text,exercises are provided at the end of each chapter.

Autoren/Hrsg.

Millar, Russell B.