Bayesian Cognitive Modeling: A Practical Course - Softcover

Lee, Michael D.

Softcover

ISBN 10: 1107603579 ISBN 13: 9781107603578

Verlag: Cambridge University Press, 2014

Inhaltsangabe

Ideal for teaching and self study, this practical book demonstrates how cognitive scientists can conduct Bayesian analyses for many real-life modeling problems. Supported by examples, exercises, computer code and additional resources available online, readers will learn to take full advantage of the exciting possibilities that the Bayesian approach affords.

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Críticas

'This book provides the best practical guide to date on how to do Bayesian modeling in cognitive science.' Jay Myung, Ohio State University

'This is a very powerful exposition of how Bayesian methods, and WinBUGS in particular, can be used to deal with cognitive models that are apparently intractable. When we produced WinBUGS, we had no idea it could be used like this - it's amazing and gratifying to see these applications.' David Spiegelhalter, Winton Professor for the Public Understanding of Risk, Statistical Laboratory, Centre for Mathematical Sciences, Cambridge

Reseña del editor

Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.

Details zur Ausgabe

• Verlag: Cambridge University Press
• Erscheinungsdatum: 2014
• ISBN 10: 1107603579
• ISBN 13: 9781107603578
• Einband: Tapa blanda
• Sprache: Englisch
• Anzahl der Seiten: 280