Click Here to Download: https://ouo.io/Fwvlns Likelihood-Free Methods for Cognitive Science By: James J. Palestro; Per B. Sederberg; Adam F. Osth; Trisha Van Zandt; Brandon M. Turner Publisher: Springer Print ISBN: 9783319724249, 331972424X eText ISBN: 9783319724256, 3319724258 Copyright year: 2018 Format: EPUB Available from $ 89.00 USD SKU 9783319724256 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-based models are now very popular in cognitive science, as are Bayesian methods for performing parameter inference. As such, the recent developments of likelihood-free techniques are an important advancement for the field. Chapters discuss the philosophy of Bayesian inference as well as provide several algorithms for performing ABC. Chapters also apply some of the algorithms in a tutorial fashion, with one specific application to the Minerva 2 model. In addition, the book discusses several applications of ABC methodology to recent problems in cognitive science. Likelihood-Free Methods for Cognitive Science will be of interest to researchers and graduate students working in experimental, applied, and cognitive science.
