Likelihood-Free Methods for Cognitive Science

• Main Authors: Palestro, James J. (Author, http://id.loc.gov/vocabulary/relators/aut), Sederberg, Per B. (http://id.loc.gov/vocabulary/relators/aut), Osth, Adam F. (http://id.loc.gov/vocabulary/relators/aut), Van Zandt, Trisha (http://id.loc.gov/vocabulary/relators/aut), Turner, Brandon M. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Computational Approaches to Cognition and Perception,
• Subjects: Cognitive psychology.; Cognitive Psychology.

This book explains the foundation of approximate Bayesian computation (ABC), an approach to Bayesian inference that does not require the specification of a likelihood function. As a result, ABC can be used to estimate posterior distributions of parameters for simulation-based models. Simulation-base...

Table of Contents:

• Chapter 1. Motivation
• Chapter 2. Likelihood-Free Algorithms
• Chapter 3. A Tutorial
• Chapter 4. Validations
• Chapter 5. Applications
• Chapter 6. Conclusions
• Chapter 7. Distributions.