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Constructing Priors that Penalize the Complexity of Gaussian Random Fields

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Cited by:

  1. Annika K. Gunderson & Rani E. Kumar & Cristina Recalde-Coronel & Luis E. Vasco & Andree Valle-Campos & Carlos F. Mena & Benjamin F. Zaitchik & Andres G. Lescano & William K. Pan & Mark M. Janko, 2020. "Malaria Transmission and Spillover across the Peru–Ecuador Border: A Spatiotemporal Analysis," IJERPH, MDPI, vol. 17(20), pages 1-9, October.
  2. Paige, John & Fuglstad, Geir-Arne & Riebler, Andrea & Wakefield, Jon, 2022. "Bayesian multiresolution modeling of georeferenced data: An extension of ‘LatticeKrig’," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
  3. Wilson, Bradley, 2020. "Evaluating the INLA-SPDE approach for Bayesian modeling of earthquake damages from geolocated cluster data," Earth Arxiv 64whm, Center for Open Science.
  4. Jonathan Wakefield & Taylor Okonek & Jon Pedersen, 2020. "Small Area Estimation for Disease Prevalence Mapping," International Statistical Review, International Statistical Institute, vol. 88(2), pages 398-418, August.
  5. C. Forlani & S. Bhatt & M. Cameletti & E. Krainski & M. Blangiardo, 2020. "A joint Bayesian space–time model to integrate spatially misaligned air pollution data in R‐INLA," Environmetrics, John Wiley & Sons, Ltd., vol. 31(8), December.
  6. Jorge Sicacha-Parada & Diego Pavon-Jordan & Ingelin Steinsland & Roel May & Bård Stokke & Ingar Jostein Øien, 2022. "A Spatial Modeling Framework for Monitoring Surveys with Different Sampling Protocols with a Case Study for Bird Abundance in Mid-Scandinavia," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 562-591, September.
  7. Andre Python & Andreas Bender & Marta Blangiardo & Janine B. Illian & Ying Lin & Baoli Liu & Tim C.D. Lucas & Siwei Tan & Yingying Wen & Davit Svanidze & Jianwei Yin, 2022. "A downscaling approach to compare COVID‐19 count data from databases aggregated at different spatial scales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 202-218, January.
  8. Youngbin Lym & Hyobin Lym & Keekwang Kim & Ki-Jung Kim, 2022. "Spatiotemporal Associations between Local Safety Level Index and COVID-19 Infection Risks across Capital Regions in South Korea," IJERPH, MDPI, vol. 19(2), pages 1-16, January.
  9. Peter A. Gao & Hannah M. Director & Cecilia M. Bitz & Adrian E. Raftery, 2022. "Probabilistic Forecasts of Arctic Sea Ice Thickness," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 280-302, June.
  10. 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.
  11. Paul B. May & Andrew O. Finley, 2025. "Calibrating Satellite Maps With Field Data for Improved Predictions of Forest Biomass," Environmetrics, John Wiley & Sons, Ltd., vol. 36(1), January.
  12. Jacqueline D. Seufert & Andre Python & Christoph Weisser & Elías Cisneros & Krisztina Kis‐Katos & Thomas Kneib, 2022. "Mapping ex ante risks of COVID‐19 in Indonesia using a Bayesian geostatistical model on airport network data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2121-2155, October.
  13. V. A. Alegana & C. Pezzulo & A. J. Tatem & B. Omar & A. Christensen, 2021. "Mapping out-of-school adolescents and youths in low- and middle-income countries," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
  14. Birgir Hrafnkelsson & Helgi Sigurdarson & Sölvi Rögnvaldsson & Axel Örn Jansson & Rafael Daníel Vias & Sigurdur M. Gardarsson, 2022. "Generalization of the power‐law rating curve using hydrodynamic theory and Bayesian hierarchical modeling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(2), March.
  15. Mahsa Nadifar & Hossein Baghishani & Afshin Fallah, 2023. "A Flexible Generalized Poisson Likelihood for Spatial Counts Constructed by Renewal Theory, Motivated by Groundwater Quality Assessment," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(4), pages 726-748, December.
  16. Wang, Craig & Furrer, Reinhard, 2021. "Combining heterogeneous spatial datasets with process-based spatial fusion models: A unifying framework," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
  17. Mauricio Campos & Bo Li & Guillaume Lafontaine & Joseph Napier & Feng Sheng Hu, 2024. "Integrating Different Data Sources Using a Bayesian Hierarchical Model to Unveil Glacial Refugia," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(3), pages 576-600, September.
  18. Guido Fioravanti & Michela Cameletti & Sara Martino & Giorgio Cattani & Enrico Pisoni, 2022. "A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID‐19 lockdown," Environmetrics, John Wiley & Sons, Ltd., vol. 33(4), June.
  19. Luis A. Barboza & Shu Wei Chou Chen & Marcela Alfaro Córdoba & Eric J. Alfaro & Hugo G. Hidalgo, 2023. "Spatio‐temporal downscaling emulator for regional climate models," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
  20. Anagh Chattopadhyay & Soudeep Deb, 2024. "A spatio-temporal model for binary data and its application in analyzing the direction of COVID-19 spread," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(4), pages 823-851, December.
  21. Oliver M. Crook & Colin T. R. Davies & Lisa M. Breckels & Josie A. Christopher & Laurent Gatto & Paul D. W. Kirk & Kathryn S. Lilley, 2022. "Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
  22. Tim C. D. Lucas & Anita K. Nandi & Elisabeth G. Chestnutt & Katherine A. Twohig & Suzanne H. Keddie & Emma L. Collins & Rosalind E. Howes & Michele Nguyen & Susan F. Rumisha & Andre Python & Rohan Ara, 2021. "Mapping malaria by sharing spatial information between incidence and prevalence data sets," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 733-749, June.
  23. Eric Yanchenko & Howard D. Bondell & Brian J. Reich, 2024. "Spatial regression modeling via the R2D2 framework," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
  24. Bondo, Kristin J. & Rosenberry, Christopher S. & Stainbrook, David & Walter, W. David, 2024. "Comparing risk of chronic wasting disease occurrence using Bayesian hierarchical spatial models and different surveillance types," Ecological Modelling, Elsevier, vol. 493(C).
  25. Paul B. May & Andrew O. Finley & Ralph O. Dubayah, 2024. "A Spatial Mixture Model for Spaceborne Lidar Observations Over Mixed Forest and Non-forest Land Types," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(4), pages 671-694, December.
  26. Xavier Barber & David Conesa & Antonio López-Quílez & Joaquín Martínez-Minaya & Iosu Paradinas & Maria Grazia Pennino, 2021. "Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach," Mathematics, MDPI, vol. 9(4), pages 1-12, February.
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