In All Likelihood: Statistical Modelling and Inference Using Likelihood

Pawitan, Yudi

ISBN 10: 0199671222 / ISBN 13: 9780199671229

Editore: Oxford University Press, 2013

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Used book in good and clean conditions. Pages and cover are intact. Limited notes marks and highlighting may be present. May show signs of normal shelf wear and bends on edges. Item may be missing CDs or access codes. May include library marks. Fast Shipping. Codice articolo ZWM.GGVQ

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Titolo: In All Likelihood: Statistical Modelling and...

Casa editrice: Oxford University Press

Data di pubblicazione: 2013

Legatura: Brossura

Condizione: good

Descrizione articolo

Riassunto:

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.

Informazioni sull?autore:

Yudi Pawitan is a Professor in the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden