Articles | Volume 2, issue 2
https://doi.org/10.5194/gchron-2-325-2020
https://doi.org/10.5194/gchron-2-325-2020
Research article
 | 
05 Nov 2020
Research article |  | 05 Nov 2020

Robust isochron calculation

Roger Powell, Eleanor C. R. Green, Estephany Marillo Sialer, and Jon Woodhead

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Revised manuscript accepted for GChron
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Cited articles

Brooks, C., Hart, S. R., and Wendt, I.: Realistic use of two-error regression treatments as applied to Rubidium-Strontium data, Rev. Geophys. Space Phys., 10, 551–577, 1972. a
Dickin, A. P.: Radiogenic isotope geology. Cambridge University Press, 492 pp., 2005. a
Fox, J.: Applied regression analysis & Generalised linear models, 3rd edn., Sage, Los Angeles, 791 pp., 2016. a
Fuller, W. A.: Measurement error models, John Wiley and Sons, 440 pp., 1987. a
Hampel, F. R., Rousseeuw, P. J., Ronchetti, E. M., and Stahel, W. A.: Robust statistics. Wiley and Sons, New York, 502 pp., 1986. a, b
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Short summary
The standard approach to isochron calculation assumes that the distribution of uncertainties on the data arising from isotopic analysis is strictly Gaussian. This excludes datasets that have more scatter, even though many appear to have age significance. Our new approach requires only that the central part of the uncertainty distribution of the data defines a "spine" in the trend of the data. A robust statistics approach is used to locate the spine, and an implementation in Python is given.