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Nonseparable, Stationary Covariance Functions for Space-Time Data

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Cited by:

  1. De Iaco, S., 2023. "Spatio-temporal generalized complex covariance models based on convolution," Computational Statistics & Data Analysis, Elsevier, vol. 183(C).
  2. Tingjin Chu & Jialuo Liu & Jun Zhu & Haonan Wang, 2022. "Spatio-Temporal Expanding Distance Asymptotic Framework for Locally Stationary Processes," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 689-713, August.
  3. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, August.
  4. André, Maïna & Dabo-Niang, Sophie & Soubdhan, Ted & Ould-Baba, Hanany, 2016. "Predictive spatio-temporal model for spatially sparse global solar radiation data," Energy, Elsevier, vol. 111(C), pages 599-608.
  5. Yasumasa Matsuda, 2014. "Wavelet Analysis Of Spatio-Temporal Data," TERG Discussion Papers 311, Graduate School of Economics and Management, Tohoku University.
  6. Aziz Ezzat, Ahmed, 2020. "Turbine-specific short-term wind speed forecasting considering within-farm wind field dependencies and fluctuations," Applied Energy, Elsevier, vol. 269(C).
  7. Mohammad Ghorbani & Ottmar Cronie & Jorge Mateu & Jun Yu, 2021. "Functional marked point processes: a natural structure to unify spatio-temporal frameworks and to analyse dependent functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 529-568, September.
  8. J. Hidalgo & M. Schafgans, 2020. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Papers 2006.14409, arXiv.org.
  9. Javier Hidalgo & Marcia M Schafgans, 2015. "Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence," STICERD - Econometrics Paper Series /2015/583, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  10. Christopher Wikle & Mevin Hooten, 2010. "A general science-based framework for dynamical spatio-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 417-451, November.
  11. An Zhang & Jinhuang Lin & Wenhui Chen & Mingshui Lin & Chengcheng Lei, 2021. "Spatial–Temporal Distribution Variation of Ground-Level Ozone in China’s Pearl River Delta Metropolitan Region," IJERPH, MDPI, vol. 18(3), pages 1-13, January.
  12. Yang, Dazhi & Gu, Chaojun & Dong, Zibo & Jirutitijaroen, Panida & Chen, Nan & Walsh, Wilfred M., 2013. "Solar irradiance forecasting using spatial-temporal covariance structures and time-forward kriging," Renewable Energy, Elsevier, vol. 60(C), pages 235-245.
  13. Nathan A. Ryder & Joshua P. Keller, 2023. "Spatiotemporal Exposure Prediction with Penalized Regression," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 260-278, June.
  14. Alessia Caponera, 2021. "SPHARMA approximations for stationary functional time series on the sphere," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 609-634, October.
  15. Hidalgo, Javier & Schafgans, Marcia, 2021. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 107426, London School of Economics and Political Science, LSE Library.
  16. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
  17. Alexander Kolovos & George Christakos, 2007. "Stastical Tools in Renewable Energy Modeling: Physical Based, Non-Separable Spatiotemporal Covariance Models," Energy and Environmental Modeling 2007 24000023, EcoMod.
  18. Yuta Kanno & Takayuki Shiohama, 2022. "Land price polarization and dispersion in Tokyo: a spatial model approach," Asia-Pacific Journal of Regional Science, Springer, vol. 6(2), pages 807-835, June.
  19. Fernández-Avilés, G & Montero, JM & Mateu, J, 2011. "Mathematical Genesis of the Spatio-Temporal Covariance Functions," MPRA Paper 35874, University Library of Munich, Germany.
  20. Yilan Luo & Deniz Sezer & David Wood & Mingkuan Wu & Hamid Zareipour, 2019. "Estimation of the Daily Variability of Aggregate Wind Power Generation in Alberta, Canada," Energies, MDPI, vol. 12(10), pages 1-29, May.
  21. P. Gregori & E. Porcu & J. Mateu & Z. Sasvári, 2008. "On potentially negative space time covariances obtained as sum of products of marginal ones," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 865-882, December.
  22. Rosa Crujeiras, 2010. "Comments on: A general science-based framework for nonlinear spatio-temporal dynamical models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 456-458, November.
  23. Moreno Bevilacqua & Christian Caamaño-Carrillo & Reinaldo B. Arellano-Valle & Camilo Gómez, 2022. "A class of random fields with two-piece marginal distributions for modeling point-referenced data with spatial outliers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 644-674, September.
  24. Steele, Fiona & Clarke, Paul & Kuha, Jouni, 2019. "Modeling within-household associations in household panel studies," LSE Research Online Documents on Economics 88162, London School of Economics and Political Science, LSE Library.
  25. I. Gede Nyoman Mindra Jaya & Henk Folmer, 2022. "Spatiotemporal high-resolution prediction and mapping: methodology and application to dengue disease," Journal of Geographical Systems, Springer, vol. 24(4), pages 527-581, October.
  26. Lim, S.C. & Teo, L.P., 2009. "Gaussian fields and Gaussian sheets with generalized Cauchy covariance structure," Stochastic Processes and their Applications, Elsevier, vol. 119(4), pages 1325-1356, April.
  27. Hidalgo, Javier & Schafgans, Marcia M. A., 2017. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 87748, London School of Economics and Political Science, LSE Library.
  28. Anup Suryawanshi & Debraj Ghosh, 2015. "Wind speed prediction using spatio-temporal covariance," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1435-1449, January.
  29. S. De Iaco & M. Palma & D. Posa, 2013. "Prediction of particle pollution through spatio-temporal multivariate geostatistical analysis: spatial special issue," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 133-150, April.
  30. Javier Hidalgo & Marcia M Schafgans, 2017. "Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence," STICERD - Econometrics Paper Series 597, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  31. José-María Montero & Gema Fernández-Avilés & Tiziana Laureti, 2021. "A Local Spatial STIRPAT Model for Outdoor NO x Concentrations in the Community of Madrid, Spain," Mathematics, MDPI, vol. 9(6), pages 1-33, March.
  32. Ip, Ryan H.L. & Li, W.K., 2017. "A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields," Statistics & Probability Letters, Elsevier, vol. 130(C), pages 115-119.
  33. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.
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