caa a22 4500 467922411 CHVBK 20180406152920.0 cr unu---uuuuu 170328e20060501xx s 000 0 eng 10.1007/s00477-005-0019-0 doi (NATIONALLICENCE)springer-10.1007/s00477-005-0019-0 Regularized kriging as a generalization of simple, universal, and bayesian kriging [Elektronische Daten] [J. Matías, W. González-Manteiga] In this article the properties of regularized kriging (RK) are studied. RK is obtained as a result of relaxing the universal kriging (UK) non-bias condition by using the support vectors methodology. More specifically, we demonstrate how RK is a continuum of solutions in function of the regularizing parameter, which includes as particular and extreme cases, simple kriging (SK) and UK, and as an intermediate case, Bayesian kriging (BK). Likewise, expressions are obtained for the mean, variance and mean squared error (MSE), as also the expression for the corresponding estimator of the coefficients of the mean. Finally, we investigate the relationship between RK and the support vector machines. By means of simulations we compare the MSE for RK with those for BK and UK, for different association models, for different levels of noise, and for differently sized mean coefficients. The RK results prove to be an improvement on the UK and BK results, and, moreover, these improvements are proportionally greater for greater levels of noise. Springer-Verlag, 2005 Bias-variance trade-off nationallicence Cauchy class nationallicence Kernel methods nationallicence Matérn class nationallicence Kriging nationallicence Support vector machines nationallicence Matías J. Department of Statistics, University of Vigo, 36200, Vigo, Spain aut González-Manteiga W. Department of Statistics, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain aut Stochastic Environmental Research and Risk Assessment Springer-Verlag 20/4(2006-05-01), 243-258 1436-3240 20:4<243 2006 20 477 https://doi.org/10.1007/s00477-005-0019-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00477-005-0019-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Matías J. Department of Statistics, University of Vigo, 36200, Vigo, Spain aut NATIONALLICENCE 700 1- González-Manteiga W. Department of Statistics, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain aut NATIONALLICENCE 773 0- Stochastic Environmental Research and Risk Assessment Springer-Verlag 20/4(2006-05-01), 243-258 1436-3240 20:4<243 2006 20 477 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer