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Variational Bayesian parameter estimation techniques for the general linear model
Date created: 2016-09-24 08:31 AM | Last Updated: 2017-09-16 06:06 AM
Identifiers: DOI 10.17605/OSF.IO/C4UX7 | ARK c7605/osf.io/c4ux7
Category: Project
Description: This project contains the Matlab code and data associated with Starke and Ostwald (2017) 'Variational Bayesian parameter estimation techniques for the general linear model'
Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespr…
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