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Article
Spatial estimation: a non-Bayesian alternative
Developmental Science (2015)
  • Hilary Barth, Wesleyan University
  • Ellen Lesser, Wesleyan University
  • Jessica Taggart, Wesleyan University
  • Emily Slusser, San Jose State University
Abstract
A large collection of estimation phenomena (e.g. biases arising when adults or children estimate remembered locations of objects in bounded spaces; Huttenlocher, Newcombe & Sandberg, 1994) are commonly explained in terms of complex Bayesian models. We provide evidence that some of these phenomena may be modeled instead by a simpler non-Bayesian alternative. Undergraduates and 9- to 10-year-olds completed a speeded linear position estimation task. Bias in both groups’ estimates could be explained in terms of a simple psychophysical model of proportion estimation. Moreover, some individual data were not compatible with the requirements of the more complex Bayesian model.
Publication Date
September, 2015
DOI
10.1111/desc.12264
Publisher Statement
This is the peer reviewed version of the following article: Barth, H., Lesser, E., Taggart, J. and Slusser, E. (2015), Spatial estimation: a non-Bayesian alternative. Developmental Science, 18: 853–862. doi: 10.1111/desc.12264, which has been published in final form at http://dx.doi.org/10.1111/desc.12264. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Citation Information
Hilary Barth, Ellen Lesser, Jessica Taggart and Emily Slusser. "Spatial estimation: a non-Bayesian alternative" Developmental Science Vol. 18 Iss. 5 (2015) p. 853 - 862 ISSN: 1363-755X
Available at: http://works.bepress.com/emily_slusser/8/