HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation m...

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Veröffentlicht in:	Frontiers in neuroinformatics Jg. 7; S. 14
Hauptverfasser:	Wiecki, Thomas V., Sofer, Imri, Frank, Michael J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 01.01.2013 Frontiers Media S.A
Schlagworte:	Bayesian analysis Bayesian modeling Computer programs Decision Making Diffusion Drift Drift diffusion model Economic models Functional magnetic resonance imaging Hypothesis testing Methods Neuroscience Neurosciences Open source software Parameter estimation python Quantitative psychology Software drift diffusion model software decision-making Bayesian modeling Python
ISSN:	1662-5196, 1662-5196
Online-Zugang:	Volltext
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