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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2019
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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’. |
format | Online Article Text |
id | pubmed-6754715 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT busemeyerjr hilbertspacemultidimensionalmodellingofcontinuousmeasurements AT wangz hilbertspacemultidimensionalmodellingofcontinuousmeasurements |