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https://link.springer.com/article/10.1007/s00477-012-0656-z
Nov 13, 2012 · Matrix-valued radially symmetric covariance functions (also called radial basis functions in the numerical analysis literature) are crucial for the analysis, inference and prediction of Gaussian... Radial basis functions with compact support for multivariate geostatistics SpringerLinkCited by: 25
https://www.researchgate.net/publication/257431755_Radial_basis_functions_with_compact_support_for_multivariate_geostatistics
Radial basis functions with compact support for multivariate geostatistics Article in Stochastic Environmental Research and Risk Assessment 27(4) · May 2012 with 47 Reads How we measure 'reads'
https://www.researchgate.net/publication/220577345_A_new_class_of_radial_basis_functions_with_compact_support
The second class of radial basis functions of compact support (Buhmann 1998 Buhmann , 2000) are reminiscent of the famous thin-plate splines, albeit truncated in a suitable way, and of a certain ...
https://projecteuclid.org/euclid.ss/1433341471
A spatial analysis of multivariate output from regional climate models Sain, Stephan R., Furrer, Reinhard, and Cressie, Noel, The Annals of Applied Statistics, 2011; A hierarchical multivariate spatio-temporal model for clustered climate data with annual cycles Mastrantonio, Gianluca, Jona Lasinio, Giovanna, Pollice, Alessio, Capotorti, Giulia, Teodonio, Lorenzo, Genova, Giulio, and Blasi ...
https://arxiv.org/pdf/1606.09527.pdf
Radial basis functions are well-known and successful tools for the interpolation of data in many dimensions [5]. Several radial basis functions of compact support that give rise to non-singular interpolation problems have been proposed, and we cite [19, 12, 5, 30, 20, 32, 33] and the impressive reviews in [8] and [21], amongst others.
https://rd.springer.com/referenceworkentry/10.1007/978-1-4899-7502-7_698-1
Jul 28, 2016 · Radial basis function networks are a means of approximation by algorithms using linear combinations of translates of a rotationally invariant function, called the radial basis function. The coefficients of these approximations usually solve a minimization problem and can also be computed by interpolation processes.
https://sbandyopadhyay.cas2.lehigh.edu/sites/sbandyopadhyay.cas2.lehigh.edu/files/LatticeKrigJCGSrevision3.pdf
1 A Multi-resolution Gaussian process model for the analysis ... 23 geostatistics and multivariate analysis. More recently the breakthroughs in Bayesian ... These radial basis functions have compact support and like 72 wavelet bases give computational e ciencies because of this feature. In our treatment,
http://scholar.google.com/citations?user=M4xlTt0AAAAJ&hl=en
This "Cited by" count includes citations to the following articles in Scholar. ... Classes of compactly supported covariance functions for multivariate random fields. DJ Daley, E Porcu, M Bevilacqua ... Radial basis functions with compact support for multivariate geostatistics. E Porcu, DJ …
https://www.sciencedirect.com/science/article/pii/S2590197419300072
Applied sciences have witnessed an explosion of georeferenced data. Object oriented spatial statistics (O2S2) is a recent system of ideas that provides a solid framework where the new challenges posed by the GeoData revolution can be faced, by grounding the analysis on a powerful geometrical and topological approach. We shall present a perspective on O2S2, as a fruitful ground where novel ...Author: Alessandra Menafoglio, Piercesare Secchi
http://www1.uni-giessen.de/www-Numerische-Mathematik/buhmann.html
``Radial basis functions with compact support for multivariate geostatistics'', Stochastic environmental research and risk assessment, to appear (mit E. Porcu, D. Daley, M. Bevilacqua). ``A note on radial basis functions interpolant limits, IMA Journal of Numerical Analysis …
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