Empirical Priors in Non-Identifiable and Sloppy Models

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This OSF project accompanies the manuscript: Spektor, M. S., & Kellen, D. (2018). The relative merit of empirical priors in non-identifiable and sloppy models: Applications to models of learning and decision-making. *Psychonomic Bulletin & Review, 25*, 2047–2068. https://doi.org/10.3758/s13423-018-1446-5 Details about the files are documented in the wikis of the respective components, **Reinforcement learning** and **Prospect theory**.

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