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Bayesian statistics to test Bayes optimality

Published online by Cambridge University Press:  10 January 2019

Brandon M. Turner Open the ORCID record for Brandon M. Turner [Opens in a new window] ,
James L. McClelland  and
Jerome Busemeyer
Brandon M. Turner
Affiliation:
Psychology Department, The Ohio State University, Columbus, OH 43210. turner.826@gmail.comhttps://turner-mbcn.com/
James L. McClelland
Affiliation:
Psychology Department, Stanford University, Stanford, CA 94305. jlmcc@stanford.eduhttps://stanford.edu/~jlmcc/
Jerome Busemeyer
Affiliation:
Psychology Department, Indiana University, Bloomington, IN 47405. jbusemey@indiana.eduhttp://mypage.iu.edu/~jbusemey/home.html
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Abstract

We agree with the authors that putting forward specific models and examining their agreement with experimental data are the best approach for understanding the nature of decision making. Although the authors only consider the likelihood function, prior, cost function, and decision rule (LPCD) framework, other choices are available. Bayesian statistics can be used to estimate essential parameters and assess the degree of optimality.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 41 , 2018 , e246
Copyright
Copyright © Cambridge University Press 2018 

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