Effective Dimensions Tend to Produce More Uncertain Estimates’. Science Advances 8 (eabn9450).

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.

Samuele Lo Piano

From Dec 1 2019 I am working in the CREDS research centre (Centre for Research into Energy Demand Solutions), flexibility theme area. My research interests include energy systems, sensitivity auditing, uncertainty quantification and global sensitivity analysis, science for governance, modelling and model (knowledge) quality assessment. My research interests also cover complexity and complex systems (such as societies).

Andrea Saltelli

Works on Sensitivity analysis, sensitivity auditing, impact assessment, science integrity, sociology of quantification, science and lobbies, science and post truth….