In All Likelihood

In All Likelihood PDF Author: Yudi Pawitan
Publisher: OUP Oxford
ISBN: 0191650587
Category : Mathematics
Languages : en
Pages : 626

Book 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.

Statistical Evidence

Statistical Evidence PDF Author: Richard Royall
Publisher: Routledge
ISBN: 1351414550
Category : Mathematics
Languages : en
Pages : 212

Book Description
Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.

Empirical Likelihood

Empirical Likelihood PDF Author: Art B. Owen
Publisher: CRC Press
ISBN: 1420036157
Category : Mathematics
Languages : en
Pages : 322

Book Description
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It al

The Likelihood Principle

The Likelihood Principle PDF Author: James O. Berger
Publisher: IMS
ISBN: 9780940600133
Category : Mathematics
Languages : en
Pages : 266

Book Description

Maximum Likelihood Estimation and Inference

Maximum Likelihood Estimation and Inference PDF Author: Russell B. Millar
Publisher: John Wiley & Sons
ISBN: 1119977711
Category : Mathematics
Languages : en
Pages : 286

Book Description
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.

Maximum Likelihood for Social Science

Maximum Likelihood for Social Science PDF Author: Michael D. Ward
Publisher: Cambridge University Press
ISBN: 1107185823
Category : Political Science
Languages : en
Pages : 327

Book Description
Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.

Probability, Statistics, and Truth

Probability, Statistics, and Truth PDF Author: Richard Von Mises
Publisher: Courier Corporation
ISBN: 0486242145
Category : Mathematics
Languages : en
Pages : 273

Book Description
This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.

Statistical Inference Based on the likelihood

Statistical Inference Based on the likelihood PDF Author: Adelchi Azzalini
Publisher: Routledge
ISBN: 1351414461
Category : Mathematics
Languages : en
Pages : 356

Book Description
The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood. Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.

Confidence, Likelihood, Probability

Confidence, Likelihood, Probability PDF Author: Tore Schweder
Publisher: Cambridge University Press
ISBN: 0521861608
Category : Business & Economics
Languages : en
Pages : 521

Book Description
This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Proudly powered by WordPress | Theme: Rits Blog by Crimson Themes.