The Power of Heterogeneity: Parameter Relationships from Distributions.
Complex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0155718&type=printable |
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| author | Magnus Röding Siobhan J Bradley Nathan H Williamson Melissa R Dewi Thomas Nann Magnus Nydén |
| author_facet | Magnus Röding Siobhan J Bradley Nathan H Williamson Melissa R Dewi Thomas Nann Magnus Nydén |
| author_sort | Magnus Röding |
| collection | DOAJ |
| description | Complex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions of individual parameters and the relationships between them, such as in nuclear magnetic resonance and optical spectroscopy. However, when data originates from different measurements and comes in different forms, resolving parameter relationships is a matter of data analysis rather than experiment. We present a method for resolving relationships between parameters that are distributed individually and also correlated. In two case studies, we model the relationships between diameter and luminescence properties of quantum dots and the relationship between molecular weight and diffusion coefficient for polymers. Although it is expected that resolving complicated correlated relationships require inherently multi-dimensional measurements, our method constitutes a useful contribution to the modelling of quantitative relationships between correlated parameters and measurements. We emphasise the general applicability of the method in fields where heterogeneity and complex distributions of parameters are obstacles to scientific insight. |
| format | Article |
| id | doaj-art-8e42569d0ed3436dbcfbf4fb003acb95 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-8e42569d0ed3436dbcfbf4fb003acb952025-08-20T03:11:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01115e015571810.1371/journal.pone.0155718The Power of Heterogeneity: Parameter Relationships from Distributions.Magnus RödingSiobhan J BradleyNathan H WilliamsonMelissa R DewiThomas NannMagnus NydénComplex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions of individual parameters and the relationships between them, such as in nuclear magnetic resonance and optical spectroscopy. However, when data originates from different measurements and comes in different forms, resolving parameter relationships is a matter of data analysis rather than experiment. We present a method for resolving relationships between parameters that are distributed individually and also correlated. In two case studies, we model the relationships between diameter and luminescence properties of quantum dots and the relationship between molecular weight and diffusion coefficient for polymers. Although it is expected that resolving complicated correlated relationships require inherently multi-dimensional measurements, our method constitutes a useful contribution to the modelling of quantitative relationships between correlated parameters and measurements. We emphasise the general applicability of the method in fields where heterogeneity and complex distributions of parameters are obstacles to scientific insight.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0155718&type=printable |
| spellingShingle | Magnus Röding Siobhan J Bradley Nathan H Williamson Melissa R Dewi Thomas Nann Magnus Nydén The Power of Heterogeneity: Parameter Relationships from Distributions. PLoS ONE |
| title | The Power of Heterogeneity: Parameter Relationships from Distributions. |
| title_full | The Power of Heterogeneity: Parameter Relationships from Distributions. |
| title_fullStr | The Power of Heterogeneity: Parameter Relationships from Distributions. |
| title_full_unstemmed | The Power of Heterogeneity: Parameter Relationships from Distributions. |
| title_short | The Power of Heterogeneity: Parameter Relationships from Distributions. |
| title_sort | power of heterogeneity parameter relationships from distributions |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0155718&type=printable |
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