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Modelplasticity and abductive decision making

‘All models are wrong but some are useful’ Box (Robustness in statistics, Elsevier, pp 201–236, 1979). But, how to find those useful ones starting from an imperfect model? How to make informed data-driven decisions equipped with an imperfect model? These fundamental questions appear to be pervasive...

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Autor principal: Mukhopadhyay, Subhadeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062281/
http://dx.doi.org/10.1007/s10203-023-00390-5
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author Mukhopadhyay, Subhadeep
author_facet Mukhopadhyay, Subhadeep
author_sort Mukhopadhyay, Subhadeep
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description ‘All models are wrong but some are useful’ Box (Robustness in statistics, Elsevier, pp 201–236, 1979). But, how to find those useful ones starting from an imperfect model? How to make informed data-driven decisions equipped with an imperfect model? These fundamental questions appear to be pervasive in virtually all empirical fields—including economics, finance, marketing, healthcare, climate change, defense planning, and operations research. This article presents a modern approach (builds on two core ideas: abductive thinking and density-sharpening principle) and practical guidelines to tackle these issues in a systematic manner. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10203-023-00390-5.
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spelling pubmed-100622812023-03-31 Modelplasticity and abductive decision making Mukhopadhyay, Subhadeep Decisions Econ Finan Article ‘All models are wrong but some are useful’ Box (Robustness in statistics, Elsevier, pp 201–236, 1979). But, how to find those useful ones starting from an imperfect model? How to make informed data-driven decisions equipped with an imperfect model? These fundamental questions appear to be pervasive in virtually all empirical fields—including economics, finance, marketing, healthcare, climate change, defense planning, and operations research. This article presents a modern approach (builds on two core ideas: abductive thinking and density-sharpening principle) and practical guidelines to tackle these issues in a systematic manner. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10203-023-00390-5. Springer International Publishing 2023-03-30 2023 /pmc/articles/PMC10062281/ http://dx.doi.org/10.1007/s10203-023-00390-5 Text en © The Author(s), under exclusive licence to Associazione per la Matematica Applicata alle Scienze Economiche e Sociali (AMASES) 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Mukhopadhyay, Subhadeep
Modelplasticity and abductive decision making
title Modelplasticity and abductive decision making
title_full Modelplasticity and abductive decision making
title_fullStr Modelplasticity and abductive decision making
title_full_unstemmed Modelplasticity and abductive decision making
title_short Modelplasticity and abductive decision making
title_sort modelplasticity and abductive decision making
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062281/
http://dx.doi.org/10.1007/s10203-023-00390-5
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