title: The Power of Heterogeneity: Parameter Relationships from Distributions.
abstract: 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.
authors.affiliation: SP Food and Bioscience, Soft Materials Science, Göteborg, Sweden.|Future Industries Institute, University of South Australia, Adelaide, Australia.|School of Energy and Resources, UCL Australia, University College London, Adelaide, Australia.
authors.forename: Magnus
authors.initials: M
authors.lastname: Röding
authors.affiliation: Future Industries Institute, University of South Australia, Adelaide, Australia.|MacDiarmid Institute, Victoria University of Wellington, Wellington, New Zealand.
authors.forename: Siobhan J
authors.initials: SJ
authors.lastname: Bradley
authors.affiliation: Future Industries Institute, University of South Australia, Adelaide, Australia.
authors.forename: Nathan H
authors.initials: NH
authors.lastname: Williamson
authors.affiliation: Future Industries Institute, University of South Australia, Adelaide, Australia.|ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Ian Wark Research Institute, University of South Australia, Adelaide, Australia.
authors.forename: Melissa R
authors.initials: MR
authors.lastname: Dewi
authors.affiliation: Future Industries Institute, University of South Australia, Adelaide, Australia.|ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Ian Wark Research Institute, University of South Australia, Adelaide, Australia.|MacDiarmid Institute, Victoria University of Wellington, Wellington, New Zealand.
authors.forename: Thomas
authors.initials: T
authors.lastname: Nann
authors.affiliation: School of Energy and Resources, UCL Australia, University College London, Adelaide, Australia.
authors.forename: Magnus
authors.initials: M
authors.lastname: Nydén
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D057225:Data Mining / Q000379:methods*; D015233:Models, Statistical