Hierarchical Bayesian Regression (HBR) and Analytic Gradient Calculation (GCGP)

Aderhold, A., Husmeier, D. and Grzegorczyk, M. (2016) Hierarchical Bayesian Regression (HBR) and Analytic Gradient Calculation (GCGP). [Data Collection]

Original publication URL: http://dx.doi.org/10.1515/sagmb-2014-0041

Collection description

The software contains two components: The HBR code and the gradient calculation code (GCGP) that uses the Gaussian Process package GPstuff (http://research.cs.aalto.fi/pml/software/gpstuff/) by:

Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, and Aki Vehtari (2013). GPstuff: Bayesian Modeling with Gaussian Processes. Journal of Machine Learning Research, 14(Apr):1175-1179

The HBR code was originally written by Marco Grzegorczyk, and adapted by Andrej Aderhold for the Biopepa data. It is located in the subfolder 'HBR/', see Section A. for details.

The GCGP code was written by Andrej Aderhold, and uses sub-routines from the GPstuff, version 4.4 software that is under the GNU GPL license. It is located in the subfolder GCGP, see Section B. for details.

Funding:
College / School: College of Science and Engineering > School of Mathematics and Statistics
Date Deposited: 09 Sep 2016 08:13
Related resources:
Statement on legal, ethical and access issues:

HBR is available for use under the following license, commonly known
as the 3-clause (or "modified") BSD license:

Copyright (c) 2013-2016 Marco Gzegorczyk and Andrej Aderhold

GCGP software is distributed under the GNU General Public License (version 3 or later); please refer to the file License.txt, included with the software, for details.

URI: https://researchdata.gla.ac.uk/id/eprint/351

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Aderhold, A., Husmeier, D. and Grzegorczyk, M. (2016); Hierarchical Bayesian Regression (HBR) and Analytic Gradient Calculation (GCGP)

University of Glasgow

DOI: 10.5525/gla.researchdata.351

Retrieved: 2024-03-19

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