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

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References

2005Gaussian Markov Random Fields1,826 cited
2008Fixed Rank Kriging for Very Large Spatial Data Sets998 cited
2008Nonstationary covariance models for global data147 cited
2007An Approach to Producing Space–Time Covariance Functions on Spheres114 cited
2007Spatial variation of total column ozone on a global scale107 cited

Cited by

2011In order to make spatial statistics computationally feasible, we need to forget about the covariance function93 cited
2018Modeling temporally evolving and spatially globally dependent data75 cited
2015Geostatistical Modelling Using Non‐Gaussian Matérn Fields67 cited

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