Yudi Pawitan

eBook, ePUB

In All Likelihood (eBook, ePUB)

Statistical Modelling and Inference Using Likelihood

Beschreibung

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.

Technische Details

• Geräte: eReader
• mit Kopierschutz
• Größe: 40MB

Barrierefreiheit

• Text-to-Speech

Autor

Yudi Pawitan graduated with a PhD in Statistics in 1987 from the University of California at Davis and has been Professor of Biostatistics since 2001 at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. He has worked in many areas of statistical applications, including time series analyses, medical imaging, and modelling and analysis of high-throughput molecular data. He has published more than 200 peer-reviewed research papers, split about equally between methodology and applied publications. He is co-author of the monograph Generalized Linear Models with Random Effects (2017) together with Youngjo Lee and John Nelder, which covers likelihood-based statistical modelling and inference in hierarchical GLMs. More recently, together with Youngjo Lee, he published Philosophies, Puzzles and Paradoxes, a book on statistical philosophy.

Produktdetails

• Verlag: OUP eBook
• Erscheinungstermin: 17. Januar 2013
• Englisch
• ISBN-13: 9780191650581
• Artikelnr.: 38146931