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March 2011 Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping
David Bolin, Finn Lindgren
Ann. Appl. Stat. 5(1): 523-550 (March 2011). DOI: 10.1214/10-AOAS383

Abstract

A new class of stochastic field models is constructed using nested stochastic partial differential equations (SPDEs). The model class is computationally efficient, applicable to data on general smooth manifolds, and includes both the Gaussian Matérn fields and a wide family of fields with oscillating covariance functions. Nonstationary covariance models are obtained by spatially varying the parameters in the SPDEs, and the model parameters are estimated using direct numerical optimization, which is more efficient than standard Markov Chain Monte Carlo procedures. The model class is used to estimate daily ozone maps using a large data set of spatially irregular global total column ozone data.

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David Bolin. Finn Lindgren. "Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping." Ann. Appl. Stat. 5 (1) 523 - 550, March 2011. https://doi.org/10.1214/10-AOAS383

Information

Published: March 2011
First available in Project Euclid: 21 March 2011

zbMATH: 1235.60075
MathSciNet: MR2810408
Digital Object Identifier: 10.1214/10-AOAS383

Keywords: Matérn covariances , Nested SPDEs , nonstationary covariances , total column ozone data

Rights: Copyright © 2011 Institute of Mathematical Statistics

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Vol.5 • No. 1 • March 2011
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