Abstract
We describe a spatial spline regression model, that efficiently deals with data distributed over irregularly shaped regions featuring complex boundaries. The model also accounts for covariate information. Efficient spline bivariate smoothing is achieved by resorting to the finite element method.
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References
Braess, D.: Finite elements (Third Edition). Cambridge University Press, Cambridge (2007)
Ramsay, J. O., Ramsay, T., Sangalli, L. M.: Spatial spline regression models. Tech. Rep. MOX, Dipartimento di Matematica, Politecnico di Milano (2011)
Ramsay, T. Spline Smoothing over Difficult Regions. J. Roy. Stat. Soc. B 64, 307–319 (2002)
Wood, S. N., Bravington, M. V., Hedley, S. L.: Soap film smoothing. J. Roy. Stat. Soc. B 70, 931–955 (2008)
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© 2011 Springer-Verlag Berlin Heidelberg
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Ramsay, J.O., Ramsay, T., Sangalli, L.M. (2011). Spatial Functional Data Analysis. In: Ferraty, F. (eds) Recent Advances in Functional Data Analysis and Related Topics. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2736-1_42
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DOI: https://doi.org/10.1007/978-3-7908-2736-1_42
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Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2735-4
Online ISBN: 978-3-7908-2736-1
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