Hierarchical Bayesian Measurement Models for Continuous Reproduction of Visual Features from Working Memory

Contributors:
  1. Colin Stoneking

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Description: Here you find R code, JAGS code, and data for the paper by Oberauer, Stoneking, Wabersich, and Lin on a hierarchical Bayesian implementation of the "mixture model" of response distributions in continuous-reproduction tasks of visual working memory, as well as for a new interference-based measurement model. The JAGS extension for the von Mises function can be downloaded here: https://github.com/yeagle/jags-vonmises/releases

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Note: Running these models requires the JAGS extension for the von Mises distribution, which you can download here: https://github.com/yeagle/jags-vonmises/releases

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