Spatial estimation: a non-Bayesian alternative

Dev Sci. 2015 Sep;18(5):853-62. doi: 10.1111/desc.12264. Epub 2014 Nov 29.

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 types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Age Factors
  • Bayes Theorem*
  • Bias*
  • Child
  • Female
  • Humans
  • Male
  • Photic Stimulation
  • Psychophysics
  • Space Perception / physiology*
  • Time Factors