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Bayesian Spatial Modeling of Extreme Precipitation Return Levels

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  1. Manuel G. Scotto & Susana M. Barbosa & Andr�s M. Alonso, 2011. "Extreme value and cluster analysis of European daily temperature series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2793-2804, March.
  2. Joaquim Henriques Vianna Neto & Alexandra M. Schmidt & Peter Guttorp, 2014. "Accounting for spatially varying directional effects in spatial covariance structures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 103-122, January.
  3. Park, Eunchun & Brorsen, Wade & Harri, Ardian, 2017. "Spatially Smoothed Crop Yield Density Estimation: Physical Distance vs Climate Similarity," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259145, Agricultural and Applied Economics Association.
  4. Wang, Yixin & So, Mike K.P., 2016. "A Bayesian hierarchical model for spatial extremes with multiple durations," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 39-56.
  5. Hongxiang Yan & Hamid Moradkhani, 2016. "Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling," 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. 81(1), pages 203-225, March.
  6. Miranda J. Fix & Daniel Cooley & Stephan R. Sain & Claudia Tebaldi, 2018. "A comparison of U.S. precipitation extremes under RCP8.5 and RCP4.5 with an application of pattern scaling," Climatic Change, Springer, vol. 146(3), pages 335-347, February.
  7. Fatima Palacios‐Rodriguez & Elena Di Bernardino & Melina Mailhot, 2023. "Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.
  8. Rishikesh Yadav & Raphaël Huser & Thomas Opitz, 2021. "Spatial hierarchical modeling of threshold exceedances using rate mixtures," Environmetrics, John Wiley & Sons, Ltd., vol. 32(3), May.
  9. Federica Stolf & Antonio Canale, 2023. "A hierarchical Bayesian non‐asymptotic extreme value model for spatial data," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
  10. Daniela Castro-Camilo & Raphaël Huser & Håvard Rue, 2019. "A Spliced Gamma-Generalized Pareto Model for Short-Term Extreme Wind Speed Probabilistic Forecasting," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 517-534, September.
  11. M. Ghil & Pascal Yiou & Stéphane Hallegatte & B. D. Malamud & P. Naveau & A. Soloviev & P. Friederichs & V. Keilis-Borok & D. Kondrashov & V. Kossobokov & O. Mestre & C. Nicolis & H. W. Rust & P. Sheb, 2011. "Extreme events: dynamics, statistics and prediction," Post-Print hal-00716514, HAL.
  12. Salaheddine El Adlouni, 2018. "Quantile regression C-vine copula model for spatial extremes," 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. 94(1), pages 299-317, October.
  13. Raphaël Huser & Marc G. Genton, 2016. "Non-Stationary Dependence Structures for Spatial Extremes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 470-491, September.
  14. Michael E. Mann & Elisabeth A. Lloyd & Naomi Oreskes, 2017. "Assessing climate change impacts on extreme weather events: the case for an alternative (Bayesian) approach," Climatic Change, Springer, vol. 144(2), pages 131-142, September.
  15. Joshua Hewitt & Miranda J. Fix & Jennifer A. Hoeting & Daniel S. Cooley, 2019. "Improved Return Level Estimation via a Weighted Likelihood, Latent Spatial Extremes Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 426-443, September.
  16. Gregory P. Bopp & Benjamin A. Shaby & Chris E. Forest & Alfonso Mejía, 2020. "Projecting Flood-Inducing Precipitation with a Bayesian Analogue Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(2), pages 229-249, June.
  17. Silius M. Vandeskog & Sara Martino & Daniela Castro-Camilo & Håvard Rue, 2022. "Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 598-621, December.
  18. Erin M. Schliep & Alan E. Gelfand & Jesús Abaurrea & Jesús Asín & María A. Beamonte & Ana C. Cebrián, 2021. "Long‐term spatial modelling for characteristics of extreme heat events," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1070-1092, July.
  19. Miranda J. Fix & Daniel S. Cooley & Emeric Thibaud, 2021. "Simultaneous autoregressive models for spatial extremes," Environmetrics, John Wiley & Sons, Ltd., vol. 32(2), March.
  20. John O'Sullivan & Conor Sweeney & Andrew C. Parnell, 2020. "Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland," Environmetrics, John Wiley & Sons, Ltd., vol. 31(5), August.
  21. K. Shuvo Bakar, 2020. "Interpolation of daily rainfall data using censored Bayesian spatially varying model," Computational Statistics, Springer, vol. 35(1), pages 135-152, March.
  22. Jill Trepanier, 2014. "Hurricane winds over the North Atlantic: spatial analysis and sensitivity to ocean temperature," 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. 71(3), pages 1733-1747, April.
  23. Jordan Richards & Jennifer L. Wadsworth, 2021. "Spatial deformation for nonstationary extremal dependence," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.
  24. N. Beck & C. Genest & J. Jalbert & M. Mailhot, 2020. "Predicting extreme surges from sparse data using a copula‐based hierarchical Bayesian spatial model," Environmetrics, John Wiley & Sons, Ltd., vol. 31(5), August.
  25. Ross Towe & Jonathan Tawn & Emma Eastoe & Rob Lamb, 2020. "Modelling the Clustering of Extreme Events for Short-Term Risk Assessment," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(1), pages 32-53, March.
  26. Park, Eunchun & Harri, Ardian & Coble, Keith H., 2022. "Estimating Crop Yield Densities for Counties with Missing Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 47(3), September.
  27. Park, Eunchun & Brorsen, B. Wade & Harri, Ardian, 2016. "Using Bayesian Spatial Smoothing and Extreme Value Theory to Develop Area-Yield Crop Insurance Rating," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235754, Agricultural and Applied Economics Association.
  28. Stephenson Alec G. & Tawn Jonathan A., 2013. "Determining the Best Track Performances of All Time Using a Conceptual Population Model for Athletics Records," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(1), pages 67-76, March.
  29. Beth Tellman & Cody Schank & Bessie Schwarz & Peter D. Howe & Alex de Sherbinin, 2020. "Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA," Sustainability, MDPI, vol. 12(15), pages 1-28, July.
  30. Chiara Bocci & Enrica Caporali & Alessandra Petrucci, 2013. "Geoadditive modeling for extreme rainfall data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 181-193, April.
  31. Linyin Cheng & Amir AghaKouchak & Eric Gilleland & Richard Katz, 2014. "Non-stationary extreme value analysis in a changing climate," Climatic Change, Springer, vol. 127(2), pages 353-369, November.
  32. Guanzhou Wei & Xiao Liu & Russell Barton, 2024. "An extended PDE‐based statistical spatio‐temporal model that suppresses the Gibbs phenomenon," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
  33. Yikuan Chen & B. Wade Brorsen & Jon T. Biermacher & Mykel Taylor, 2022. "Spatially varying wheat protein premiums," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 587-598, December.
  34. Jonathan Jalbert & Christian Genest & Luc Perreault, 2022. "Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 461-486, September.
  35. Sweta Rai & Alexis Hoffman & Soumendra Lahiri & Douglas W. Nychka & Stephan R. Sain & Soutir Bandyopadhyay, 2024. "Fast parameter estimation of generalized extreme value distribution using neural networks," Environmetrics, John Wiley & Sons, Ltd., vol. 35(3), May.
  36. Hongxiang Yan & Hamid Moradkhani, 2016. "Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling," 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. 81(1), pages 203-225, March.
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