Efficient Approximation of the Spatial Covariance Function for Large Datasets - Analysis of Atmospheric CO2 Concentrations
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References listed on IDEAS
- Kaufman, Cari G. & Schervish, Mark J. & Nychka, Douglas W., 2008. "Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1545-1555.
- Noel Cressie & Gardar Johannesson, 2008. "Fixed rank kriging for very large spatial data sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 209-226.
- Huiyan Sang & Jianhua Z. Huang, 2012. "A full scale approximation of covariance functions for large spatial data sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(1), pages 111-132, January.
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- Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2016. "Spatio-temporal statistical assessment of anthropogenic CO2 emissions from satellite data," Discussion Paper Series RECAP15 24, RECAP15, European University Viadrina, Frankfurt (Oder).
More about this item
Keywordsspatial covariance function; fixed rank kriging; covariance tapering; full-scale approximation; large spatial data sets; mid-tropospheric CO2; remote sensing; efficient approximation;
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2013-08-31 (All new papers)
- NEP-ECM-2013-08-31 (Econometrics)
- NEP-ENE-2013-08-31 (Energy Economics)
- NEP-ENV-2013-08-31 (Environmental Economics)
- NEP-GEO-2013-08-31 (Economic Geography)
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