Abstract
Dimensional Analysis can make a contribution to data modelling when some of the variables in the problem are physical. The analysis constructs the set of independent dimensionless factors that should be used as the major variables of the model in place of the original measurements. There are fewer of these than the originals and they may have a more appropriate interpretation. The technique is described briefly and its proposed role in data analysis and regression illustrated with an example.
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© 1992 Springer Science+Business Media Dordrecht
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Vignaux, G.A. (1992). Dimensional Analysis in Data Modelling. In: Smith, C.R., Erickson, G.J., Neudorfer, P.O. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 50. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2219-3_7
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DOI: https://doi.org/10.1007/978-94-017-2219-3_7
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4220-0
Online ISBN: 978-94-017-2219-3
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