Maximum Likelihood Estimation and Inference
eBook - ePub

Maximum Likelihood Estimation and Inference

With Examples in R, SAS and ADMB

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Maximum Likelihood Estimation and Inference

With Examples in R, SAS and ADMB

About this book

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm.

Key features:

  • Provides an accessible introduction to pragmatic maximum likelihood modelling.
  • Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood.
  • Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data.
  • Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology.
  • Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB.
  • Provides all program code and software extensions on a supporting website.
  • Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters.

  

This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.

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Yes, you can access Maximum Likelihood Estimation and Inference by Russell B. Millar in PDF and/or ePUB format, as well as other popular books in Matemáticas & Probabilidad y estadística. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2011
Print ISBN
9780470094822
eBook ISBN
9781119977711

Table of contents

  1. Cover
  2. Statistics in Practice
  3. Title Page
  4. Copyright
  5. Preface
  6. Part I: Preliminaries
  7. Part II: Pragmatics
  8. Part III: Theoretical Foundations
  9. Appendix: Partial solutions to selected exercises
  10. Bibliography
  11. Index
  12. Statistics in Practice