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Bayesian Cognitive Modeling: A Practical Course

  • Livre Relié
  • 280 Nombre de pages
Informationen zum Autor Michael D. Lee is a professor in the Department of Cognitive Sciences at the University of California, Irv... Lire la suite
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Description

Informationen zum Autor Michael D. Lee is a professor in the Department of Cognitive Sciences at the University of California, Irvine. Eric-Jan Wagenmakers is a professor in the Department of Psychological Methods at the University of Amsterdam. Klappentext Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results. Zusammenfassung Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results. Inhaltsverzeichnis Part I. Getting Started: 1. The basics of Bayesian analysis; 2. Getting started with WinBUGS; Part II. Parameter Estimation: 3. Inferences with binomials; 4. Inferences with Gaussians; 5. Some examples of data analysis; 6. Latent mixture models; Part III. Model Selection: 7. Bayesian model comparison; 8. Comparing Gaussian means; 9. Comparing binomial rates; Part IV. Case Studies: 10. Memory retention; 11. Signal detection theory; 12. Psychophysical functions; 13. Extrasensory perception; 14. Multinomial processing trees; 15. The SIMPLE model of memory; 16. The BART model of risk taking; 17. The GCM model of categorization; 18. Heuristic decision-making; 19. Number concept development.

Texte du rabat

Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results.



Contenu

Part I. Getting Started: 1. The basics of Bayesian analysis; 2. Getting started with WinBUGS; Part II. Parameter Estimation: 3. Inferences with binomials; 4. Inferences with Gaussians; 5. Some examples of data analysis; 6. Latent mixture models; Part III. Model Selection: 7. Bayesian model comparison; 8. Comparing Gaussian means; 9. Comparing binomial rates; Part IV. Case Studies: 10. Memory retention; 11. Signal detection theory; 12. Psychophysical functions; 13. Extrasensory perception; 14. Multinomial processing trees; 15. The SIMPLE model of memory; 16. The BART model of risk taking; 17. The GCM model of categorization; 18. Heuristic decision-making; 19. Number concept development.

Détails sur le produit

Titre: Bayesian Cognitive Modeling: A Practical Course
Sous-titre: A Practical Course
Auteur:
Code EAN: 9781107018457
ISBN: 978-1-107-01845-7
Format: Livre Relié
Editeur: Cambridge Univ Pr
Genre: Psychologie
nombre de pages: 280
Poids: 703g
Taille: H249mm x B188mm x T20mm
Année: 2014
Auflage: New