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Hilbert space multidimensional modelling of continuous measurements

Data fusion problems arise when a researcher needs to analyse results obtained by measuring empirical variables under different measurement contexts. A context is defined by a subset of variables taken from a complete set of variables under investigation. Multiple contexts can be formed from differe...

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Detalles Bibliográficos
Autores principales: Busemeyer, J. R., Wang, Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754715/
https://www.ncbi.nlm.nih.gov/pubmed/31522635
http://dx.doi.org/10.1098/rsta.2019.0142
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author Busemeyer, J. R.
Wang, Z.
author_facet Busemeyer, J. R.
Wang, Z.
author_sort Busemeyer, J. R.
collection PubMed
description Data fusion problems arise when a researcher needs to analyse results obtained by measuring empirical variables under different measurement contexts. A context is defined by a subset of variables taken from a complete set of variables under investigation. Multiple contexts can be formed from different subsets, which produce a separate distribution of measurements associated with each context. A context effect occurs when the distributions produced by the different contexts cannot be reproduced by marginalizing over a complete joint distribution formed by all the variables. We propose a Hilbert space multidimensional theory that uses a state vector and measurement operators to account for multiple distributions produced by different contexts. This article is part of the theme issue ‘Contextuality and probability in quantum mechanics and beyond’.
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spelling pubmed-67547152019-09-22 Hilbert space multidimensional modelling of continuous measurements Busemeyer, J. R. Wang, Z. Philos Trans A Math Phys Eng Sci Articles Data fusion problems arise when a researcher needs to analyse results obtained by measuring empirical variables under different measurement contexts. A context is defined by a subset of variables taken from a complete set of variables under investigation. Multiple contexts can be formed from different subsets, which produce a separate distribution of measurements associated with each context. A context effect occurs when the distributions produced by the different contexts cannot be reproduced by marginalizing over a complete joint distribution formed by all the variables. We propose a Hilbert space multidimensional theory that uses a state vector and measurement operators to account for multiple distributions produced by different contexts. This article is part of the theme issue ‘Contextuality and probability in quantum mechanics and beyond’. The Royal Society Publishing 2019-11-04 2019-09-16 /pmc/articles/PMC6754715/ /pubmed/31522635 http://dx.doi.org/10.1098/rsta.2019.0142 Text en © 2019 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Busemeyer, J. R.
Wang, Z.
Hilbert space multidimensional modelling of continuous measurements
title Hilbert space multidimensional modelling of continuous measurements
title_full Hilbert space multidimensional modelling of continuous measurements
title_fullStr Hilbert space multidimensional modelling of continuous measurements
title_full_unstemmed Hilbert space multidimensional modelling of continuous measurements
title_short Hilbert space multidimensional modelling of continuous measurements
title_sort hilbert space multidimensional modelling of continuous measurements
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754715/
https://www.ncbi.nlm.nih.gov/pubmed/31522635
http://dx.doi.org/10.1098/rsta.2019.0142
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