Constructing informative model priors using hierarchical methods

DOI10.1016/j.jmp.2010.08.005zbMath1208.62195OpenAlexW2060112995MaRDI QIDQ631951

Wolf Vanpaemel

Publication date: 14 March 2011

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/308226

zbMATH Keywords

estimationabstractionpriorscategory learningsubjectiveinformative

Mathematics Subject Classification ID

Bayesian inference (62F15) Applications of statistics to psychology (62P15)

Related Items (7)

Empirical priors for reinforcement learning models ⋮ Prototypes, exemplars and the response scaling parameter: a Bayes factor perspective ⋮ Using Bayes factors to test the predictions of models: a case study in visual working memory ⋮ Approaches to analysis in model-based cognitive neuroscience ⋮ Algebraic aspects of Bayesian modeling in psychology ⋮ How cognitive modeling can benefit from hierarchical Bayesian models ⋮ Thermodynamic integration and steppingstone sampling methods for estimating Bayes factors: a tutorial

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