Beyond chi-squared: Additional measures of the closeness of a model to data

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Abstract

Subtle, and not so subtle, features in our increasingly large and complex datasets are being missed because of our reliance on a single number, typically chi-squared based, to describe the distance between a plausible model and the data. Additional measures need to be used. Here I propose that the autocorrelations of the residuals between the data and the model responses be minimized as part of the objective function during inversion. I demonstrate the use on a toy example and three 1D magnetotelluric examples, one a synthetic “impossible” problem and two real ones.

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Jones, A. G. (2018). Beyond chi-squared: Additional measures of the closeness of a model to data. Exploration Geophysics, 2019(1), 1–6. https://doi.org/10.1080/22020586.2019.12072970

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