Synthese 190 (2):203-218 (2013)

Authors
Brian Epstein
Tufts University
Patrick Forber
Tufts University
Abstract
When can macroscopic data about a system be used to set parameters in a microfoundational simulation? We examine the epistemic viability of tweaking parameter values to generate a better fit between the outcome of a simulation and the available observational data. We restrict our focus to microfoundational simulations—those simulations that attempt to replicate the macrobehavior of a target system by modeling interactions between microentities. We argue that tweaking can be effective but that there are two central risks. First, tweaking risks overfitting the simulation to the data and thus compromising predictive accuracy; and second, it risks compromising the microfoundationality of the simulation. We evaluate standard responses to tweaking and propose strategies to guard against these risks.
Keywords Microfoundations  Overfitting  Tuning  Calibration  Simulation  Estimation
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DOI 10.1007/s11229-012-0142-7
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References found in this work BETA

Thinking About Mechanisms.Peter Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
Theory and Evidence.Clark N. Glymour - 1980 - Princeton University Press.
Prediction Versus Accommodation and the Risk of Overfitting.Christopher Hitchcock & Elliott Sober - 2004 - British Journal for the Philosophy of Science 55 (1):1-34.

View all 10 references / Add more references

Citations of this work BETA

The Argument From Surprise.Adrian Currie - 2018 - Canadian Journal of Philosophy 48 (5):639-661.
Empirical Agreement in Model Validation.Julie Jebeile & Anouk Barberousse - 2016 - Studies in History and Philosophy of Science Part A 56:168-174.

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