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Updated: Aug 25, 2025

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Models with higher effective dimensions tend to produce more uncertain estimates
Arnald Puy1,2,3, Pierfrancesco Beneventano4, Simon A Levin2
1School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK.
Abstract:
Mathematical models are getting increasingly detailed to better predict phenomena or gain more accurate insights into the dynamics of a system of interest, even when there are no validation or training data available. Here, we show through ANOVA and statistical theory that this practice promotes fuzzier estimates because it generally increases the model's effective dimensions, i.e., the number of influential parameters and the weight of high-order interactions. By tracking the evolution of the effective dimensions and the output uncertainty at each model upgrade stage, modelers can better ponder whether the addition of detail truly matches the model's purpose and the quality of the data fed into it.
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