{"title":"What are the Bayesian constraints in the Bayesian reader? Reply to Norris and Kinoshita (2010)","authors":"J. Bowers","doi":"10.1080/09541446.2010.532120","DOIUrl":null,"url":null,"abstract":"In this brief reply, I argue that the Bayesian reader can account for any pattern of data (including those not actually observed) because the predictions of the model are largely independent of any Bayesian principles. It is a good thing that the model is flexible, as the implemented model has been falsified by existing data.","PeriodicalId":88321,"journal":{"name":"The European journal of cognitive psychology","volume":"31 1","pages":"1270 - 1273"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The European journal of cognitive psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09541446.2010.532120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this brief reply, I argue that the Bayesian reader can account for any pattern of data (including those not actually observed) because the predictions of the model are largely independent of any Bayesian principles. It is a good thing that the model is flexible, as the implemented model has been falsified by existing data.
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