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Bayesian Inference in MANTID - An Update

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10.1088/1742-6596/1021/1/012012
 
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Vidal, B.L.
Oram, E.
Banos, R.A.
Pardo Soto, Luis CarlosMés informacióMés informacióMés informació
Mukhopadhyay, Sajal
Fernandez Alonso, Felix
Document typeConference report
Defense date2018
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
In the context of neutron science, Bayesian inference methods have been recently implemented within the MANTID framework [Monserrat D et al. 2015 J. Phys. Conf. Ser. 663 012009 (2015)]. In this contribution, we highlight the advantages of this software package for robust data analysis and subsequent model selection. To this end, we use the celebrated Rosenbrock function to illustrate its merits and strengths relative to classical fitting algorithms. We also introduce the latest additions implemented in MANTID, with a view to increasing its user friendliness as well as stimulating wider use. These include simulated-annealing schemes to reduce the need for initial guesses, as well as new options for multidimensional fitting. © Published under licence by IOP Publishing Ltd.
CitationVidal, B., Oram, E., Banos, R., Pardo, L., Mukhopadhyay, S., Fernandez-Alonso, F. Bayesian Inference in MANTID - An Update. A: International Collaboration on Advanced Neutron Sources. "Journal of Physics: Conference Series". 2018. 
URIhttp://hdl.handle.net/2117/124751
DOI10.1088/1742-6596/1021/1/012012
ISBN17426588
Publisher versionhttp://iopscience.iop.org/article/10.1088/1742-6596/1021/1/012012/meta
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