date: 2017-09-21T07:55:14Z
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pdf:docinfo:title: Variational Bayesian Parameter Estimation Techniques for the General Linear Model
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subject: 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.
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dc:title: Variational Bayesian Parameter Estimation Techniques for the General Linear Model
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cp:subject: 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.
pdf:docinfo:subject: 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.
pdf:docinfo:creator: Dirk Ostwald
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dc:description: 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.
Keywords: variational Bayes, general linear model (GLM), fMRI neuroimaging, restricted maximum likelihood estimation, covariance estimation, data analysis, machine learning
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dc:creator: Dirk Ostwald
description: 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.
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title: Variational Bayesian Parameter Estimation Techniques for the General Linear Model
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