Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- 1 Principles and Consequences of the Initial Visual Encoding
- 2 Measuring Multisensory Integration in Selected Paradigms
- 3 Fechnerian Scaling: Dissimilarity Cumulation Theory
- 4 Mathematical Models of Human Learning
- 5 Formal Models of Memory Based on Temporally-Varying Representations
- 6 Statistical Decision Theory
- 7 Modeling Response Inhibition in the Stop-Signal Task
- 8 Approximate Bayesian Computation
- 9 Cognitive Diagnosis Models
- 10 Encoding Models in Neuroimaging
- Index
8 - Approximate Bayesian Computation
Published online by Cambridge University Press: 20 April 2023
Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- 1 Principles and Consequences of the Initial Visual Encoding
- 2 Measuring Multisensory Integration in Selected Paradigms
- 3 Fechnerian Scaling: Dissimilarity Cumulation Theory
- 4 Mathematical Models of Human Learning
- 5 Formal Models of Memory Based on Temporally-Varying Representations
- 6 Statistical Decision Theory
- 7 Modeling Response Inhibition in the Stop-Signal Task
- 8 Approximate Bayesian Computation
- 9 Cognitive Diagnosis Models
- 10 Encoding Models in Neuroimaging
- Index
Summary
Approximate Bayesian analysis is presented as the solution for complex computational models where no explicit maximum likelihood estimation is possible. The activation-suppression racemodel (ASR), which does have a likelihood amenable to Markov chain Monte Carlo methods, is used to demonstrate the accuracy with which parameters can be estimated with the approximate Bayesian methods.
- Type
- Chapter
- Information
- New Handbook of Mathematical Psychology , pp. 357 - 384Publisher: Cambridge University PressPrint publication year: 2023