D-STEM: A Software for the Analysis and Mapping of Environmental Space-Time Variables
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DOI: http://hdl.handle.net/10.18637/jss.v062.i06
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References listed on IDEAS
- Tatiyana V. Apanasovich & Marc G. Genton, 2010. "Cross-covariance functions for multivariate random fields based on latent dimensions," Biometrika, Biometrika Trust, vol. 97(1), pages 15-30.
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- Matthias Katzfuss & Noel Cressie, 2011. "Spatio‐temporal smoothing and EM estimation for massive remote‐sensing data sets," Journal of Time Series Analysis, Wiley Blackwell, vol. 32, pages 430-446, July.
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- Fassò, A. & Finazzi, F. & Madonna, F., 2018. "Statistical issues in radiosonde observation of atmospheric temperature and humidity profiles," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 97-100.
- Francesco Finazzi, 2020. "Fulfilling the information need after an earthquake: statistical modelling of citizen science seismic reports for predicting earthquake parameters in near realtime," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 857-882, June.
- Alessandro Fassò & Francesco Finazzi & Ferdinand Ndongo, 2016. "European Population Exposure to Airborne Pollutants Based on a Multivariate Spatio-Temporal Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 492-511, September.
- Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2016.
"Spatio-temporal statistical analysis of the carbon budget of the terrestrial ecosystem,"
Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 143-161, March.
- Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2016. "Spatio-temporal statistical analysis of the carbon budget of the terrestrial ecosystem," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 143-161, March.
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