Abstract
We develop a Bayesian approach to the interpolation problem, returning a probability distribution over interpolating functions as our inference. The approach provides a means of determining the optimal correlation length-scales that arise in the assumptions made about spatial correlation in the underlying function as well as an objective comparison of different correlation assumptions.
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References
Buhmann, M.D., M.J.D. Powell: 1990, ‘Radial Basis Function Interpolation on an Infinite Regular Grid’, in Algorithms for Approximation II, J.C. Mason, M.G. Cox, Chapman, and Hall (eds.), 146–169.
Gull, S.F.: 1989, ‘Developments in Maximum Entropy Data Analysis’, in Maximum Entropy and Bayesian Methods, J. Skilling (ed.), Kluwer, 53–71.
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© 1991 Springer Science+Business Media Dordrecht
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Sibisi, S. (1991). Bayesian Interpolation. In: Grandy, W.T., Schick, L.H. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 43. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3460-6_35
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DOI: https://doi.org/10.1007/978-94-011-3460-6_35
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-5531-4
Online ISBN: 978-94-011-3460-6
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