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Bayesian Inference in MANTID - An Update
dc.contributor.author | Vidal, B.L. |
dc.contributor.author | Oram, E. |
dc.contributor.author | Banos, R.A. |
dc.contributor.author | Pardo Soto, Luis Carlos |
dc.contributor.author | Mukhopadhyay, Sajal |
dc.contributor.author | Fernandez Alonso, Felix |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Física |
dc.date.accessioned | 2018-11-20T13:11:38Z |
dc.date.available | 2018-11-20T13:11:38Z |
dc.date.issued | 2018 |
dc.identifier.citation | Vidal, 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. |
dc.identifier.isbn | 17426588 |
dc.identifier.uri | http://hdl.handle.net/2117/124751 |
dc.description.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. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Física |
dc.subject.lcsh | Bayesian statistical decision theory |
dc.subject.lcsh | Neutrons |
dc.subject.other | Inference engines |
dc.subject.other | International cooperation |
dc.subject.other | Neutron sources |
dc.subject.other | Neutrons |
dc.subject.other | Simulated annealing |
dc.subject.other | Bayesian inference |
dc.subject.other | Fitting algorithms |
dc.subject.other | Initial guess |
dc.subject.other | Model Selection |
dc.subject.other | Neutron science |
dc.subject.other | New options |
dc.subject.other | Rosenbrock functions |
dc.subject.other | User friendliness |
dc.subject.other | Bayesian networks |
dc.title | Bayesian Inference in MANTID - An Update |
dc.type | Conference report |
dc.subject.lemac | Estadística bayesiana |
dc.subject.lemac | Neutrons |
dc.contributor.group | Universitat Politècnica de Catalunya. GCM - Grup de Caracterització de Materials |
dc.identifier.doi | 10.1088/1742-6596/1021/1/012012 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://iopscience.iop.org/article/10.1088/1742-6596/1021/1/012012/meta |
dc.rights.access | Open Access |
local.identifier.drac | 23420736 |
dc.description.version | Postprint (published version) |
local.citation.author | Vidal, B.; Oram, E.; Banos, R.; Pardo, L.; Mukhopadhyay, S.; Fernandez-Alonso, F. |
local.citation.contributor | International Collaboration on Advanced Neutron Sources |
local.citation.publicationName | Journal of Physics: Conference Series |