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Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping


Reference:

Bolin, D. and Lindgren, F., 2011. Spatial models generated by nested stochastic partial differential equations, with an application to global ozone mapping. Annals of Applied Statistics, 5 (1), pp. 523-550.

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    Official URL:

    http://dx.doi.org/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.

    Details

    Item Type Articles
    CreatorsBolin, D.and Lindgren, F.
    DOI10.1214/10-AOAS383
    DepartmentsFaculty of Science > Mathematical Sciences
    RefereedYes
    StatusPublished
    ID Code32285

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