The geometry of sloppiness

Dufresne, Emilie and Harrington, Heather A. and Raman, Dhruva V. (2018) The geometry of sloppiness. Journal of Algebraic Statistics . ISSN 1309-3452 (In Press)

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Abstract

The use of mathematical models in the sciences often involves the estimation of unknown parameter values from data. Sloppiness provides information about the uncertainty of this task. In this paper, we develop a precise mathematical foundation for sloppiness as initially introduced and define rigorously key concepts, such as `model manifold', in relation to concepts of structural identifiability. We redefine sloppiness conceptually as a comparison between the premetric on parameter space induced by measurement noise and a reference metric. This opens up the possibility of alternative quantification of sloppiness, beyond the standard use of the Fisher Information Matrix, which assumes that parameter space is equipped with the usual Euclidean metric and the measurement error is infinitesimal. Applications include parametric statistical models, explicit time dependent models, and ordinary differential equation models.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Related URLs:
URLURL Type
https://jalgstat.library.iit.edu/?journal=jalgstat&page=indexUNSPECIFIED
Depositing User: Eprints, Support
Date Deposited: 04 Sep 2018 08:49
Last Modified: 04 Sep 2018 09:03
URI: http://eprints.nottingham.ac.uk/id/eprint/53659

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