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Sensitivity measures based on scoring functions

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  • Fissler, Tobias
  • Pesenti, Silvana M.

Abstract

We propose a holistic framework for constructing sensitivity measures for any elicitable functional T of a response variable. The sensitivity measures, termed score-based sensitivities, are constructed via scoring functions that are (strictly) consistent for T. These score-based sensitivities quantify the relative improvement in predictive accuracy when available information, e.g., from explanatory variables, is used ideally. We establish intuitive and desirable properties of these sensitivities and discuss advantageous choices of scoring functions leading to scale-invariant sensitivities.

Suggested Citation

  • Fissler, Tobias & Pesenti, Silvana M., 2023. "Sensitivity measures based on scoring functions," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1408-1423.
    • Handle: RePEc:eee:ejores:v:307:y:2023:i:3:p:1408-1423
    DOI: 10.1016/j.ejor.2022.10.002
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    Cited by:

    1. Sebastian Jaimungal & Silvana M. Pesenti, 2024. "Kullback-Leibler Barycentre of Stochastic Processes," Papers 2407.04860, arXiv.org.
    2. Silvana M. Pesenti & Steven Vanduffel, 2023. "Optimal Transport Divergences induced by Scoring Functions," Papers 2311.12183, arXiv.org, revised Apr 2024.
    3. Silvana M. Pesenti & Pietro Millossovich & Andreas Tsanakas, 2023. "Differential Quantile-Based Sensitivity in Discontinuous Models," Papers 2310.06151, arXiv.org, revised Oct 2024.

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