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An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach

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Cited by:

  1. Rajala, T. & Penttinen, A., 2014. "Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 530-541.
  2. Qian Ren & Sudipto Banerjee, 2013. "Hierarchical Factor Models for Large Spatially Misaligned Data: A Low-Rank Predictive Process Approach," Biometrics, The International Biometric Society, vol. 69(1), pages 19-30, March.
  3. K. Shuvo Bakar & Nicholas Biddle & Philip Kokic & Huidong Jin, 2020. "A Bayesian spatial categorical model for prediction to overlapping geographical areas in sample surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 535-563, February.
  4. G. Mateo, Rubén & Aroca-Fernández, María José & Gastón, Aitor & Gómez-Rubio, Virgilio & Saura, Santiago & García-Viñas, Juan Ignacio, 2019. "Looking for an optimal hierarchical approach for ecologically meaningful niche modelling," Ecological Modelling, Elsevier, vol. 409(C), pages 1-1.
  5. Samira Zahmatkesh & Mohsen Mohammadzadeh, 2021. "Bayesian prediction of spatial data with non-ignorable missingness," Statistical Papers, Springer, vol. 62(5), pages 2247-2268, October.
  6. Athanasios Christou Micheas, 2014. "Hierarchical Bayesian modeling of marked non-homogeneous Poisson processes with finite mixtures and inclusion of covariate information," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(12), pages 2596-2615, December.
  7. Laura M. Sangalli, 2021. "Spatial Regression With Partial Differential Equation Regularisation," International Statistical Review, International Statistical Institute, vol. 89(3), pages 505-531, December.
  8. 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).
  9. Fasil Wagnew & Kefyalew Addis Alene & Matthew Kelly & Darren Gray, 2023. "Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia," IJERPH, MDPI, vol. 20(21), pages 1-15, October.
  10. Behnaz Pirzamanbein & Johan Lindström, 2022. "Reconstruction of past human land use from pollen data and anthropogenic land cover changes," Environmetrics, John Wiley & Sons, Ltd., vol. 33(6), September.
  11. Monterrubio-Gómez, Karla & Roininen, Lassi & Wade, Sara & Damoulas, Theodoros & Girolami, Mark, 2020. "Posterior inference for sparse hierarchical non-stationary models," Computational Statistics & Data Analysis, Elsevier, vol. 148(C).
  12. Castruccio, Stefano & Genton, Marc G., 2018. "Principles for statistical inference on big spatio-temporal data from climate models," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 92-96.
  13. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
  14. Seppo Virtanen & Mark Girolami, 2021. "Spatio‐temporal mixed membership models for criminal activity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1220-1244, October.
  15. Daniel Cervone & Alex D’Amour & Luke Bornn & Kirk Goldsberry, 2016. "A Multiresolution Stochastic Process Model for Predicting Basketball Possession Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 585-599, April.
  16. Laura Azzimonti & Laura M. Sangalli & Piercesare Secchi & Maurizio Domanin & Fabio Nobile, 2015. "Blood Flow Velocity Field Estimation Via Spatial Regression With PDE Penalization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1057-1071, September.
  17. Stefano Castruccio & Joseph Guinness, 2017. "An evolutionary spectrum approach to incorporate large-scale geographical descriptors on global processes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 329-344, February.
  18. Humphreys, John M. & Elsner, James B. & Jagger, Thomas H. & Pau, Stephanie, 2017. "A Bayesian geostatistical approach to modeling global distributions of Lygodium microphyllum under projected climate warming," Ecological Modelling, Elsevier, vol. 363(C), pages 192-206.
  19. Walder, Adam & Hanks, Ephraim M., 2020. "Bayesian analysis of spatial generalized linear mixed models with Laplace moving average random fields," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  20. Lindgren, Finn & Rue, Håvard, 2015. "Bayesian Spatial Modelling with R-INLA," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i19).
  21. John M. Humphreys & Robert B. Srygley & David H. Branson, 2022. "Geographic Variation in Migratory Grasshopper Recruitment under Projected Climate Change," Geographies, MDPI, vol. 2(1), pages 1-19, January.
  22. Paciorek, Christopher J. & Lipshitz, Benjamin & Zhuo, Wei & Prabhat, . & Kaufman, Cari G. G. & Thomas, Rollin C., 2015. "Parallelizing Gaussian Process Calculations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i10).
  23. Klein, Nadja & Herwartz, Helmut & Kneib, Thomas, 2020. "Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales," Journal of Econometrics, Elsevier, vol. 214(2), pages 513-539.
  24. Ying C. MacNab, 2018. "Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 497-541, September.
  25. Marchetti, Yuliya & Nguyen, Hai & Braverman, Amy & Cressie, Noel, 2018. "Spatial data compression via adaptive dispersion clustering," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 138-153.
  26. Liam Lachs & Simon D. Donner & Peter J. Mumby & John C. Bythell & Adriana Humanes & Holly K. East & James R. Guest, 2023. "Emergent increase in coral thermal tolerance reduces mass bleaching under climate change," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  27. Francesco Serafini & Finn Lindgren & Mark Naylor, 2023. "Approximation of Bayesian Hawkes process with inlabru," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
  28. Laia Maynou & Javier Ordóñez & José Ignacio Silva, 2020. "NEET rates convergence in Europe: A regional analysis," Working Papers 2020/08, Economics Department, Universitat Jaume I, Castellón (Spain).
  29. Matthias Katzfuss & Joseph Guinness & Wenlong Gong & Daniel Zilber, 2020. "Vecchia Approximations of Gaussian-Process Predictions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 383-414, September.
  30. Diego Varga & Mariona Roigé & Josep Pintó & Marc Saez, 2019. "Assessing the Spatial Distribution of Biodiversity in a Changing Temperature Pattern: The Case of Catalonia, Spain," IJERPH, MDPI, vol. 16(20), pages 1-13, October.
  31. William Kleiber & Stephan Sain & Luke Madaus & Patrick Harr, 2023. "Stochastic tropical cyclone precipitation field generation," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
  32. Aaron Osgood‐Zimmerman & Jon Wakefield, 2023. "A Statistical Review of Template Model Builder: A Flexible Tool for Spatial Modelling," International Statistical Review, International Statistical Institute, vol. 91(2), pages 318-342, August.
  33. Somnath Chaudhuri & Gerard Giménez-Adsuar & Marc Saez & Maria A. Barceló, 2022. "PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain," IJERPH, MDPI, vol. 19(8), pages 1-22, April.
  34. Morales-Oñate, Víctor & Crudu, Federico & Bevilacqua, Moreno, 2021. "Blockwise Euclidean likelihood for spatio-temporal covariance models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 176-201.
  35. Daniel Vélez-Serrano & Alejandro Álvaro-Meca & Fernando Sebastián-Huerta & Jose Vélez-Serrano, 2021. "Spatio-Temporal Traffic Flow Prediction in Madrid: An Application of Residual Convolutional Neural Networks," Mathematics, MDPI, vol. 9(9), pages 1-16, May.
  36. Finn Lindgren, 2015. "Comments on: Comparing and selecting spatial predictors using local criteria," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 35-44, March.
  37. 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.
  38. Alberto Rodríguez-Casal & Paula Saavedra-Nieves, 2022. "Spatial distribution of invasive species: an extent of occurrence approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 416-441, June.
  39. T. Subba Rao & Gyorgy Terdik, 2017. "A New Covariance Function and Spatio-Temporal Prediction (Kriging) for A Stationary Spatio-Temporal Random Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 936-959, November.
  40. Anteneh Asmare Godana & Samuel Musili Mwalili & George Otieno Orwa, 2019. "Dynamic spatiotemporal modeling of the infected rate of visceral leishmaniasis in human in an endemic area of Amhara regional state, Ethiopia," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-21, March.
  41. 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.
  42. Carson, Stuart & Mills Flemming, Joanna, 2014. "Seal encounters at sea: A contemporary spatial approach using R-INLA," Ecological Modelling, Elsevier, vol. 291(C), pages 175-181.
  43. David L. Miller & Richard Glennie & Andrew E. Seaton, 2020. "Understanding the Stochastic Partial Differential Equation Approach to Smoothing," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(1), pages 1-16, March.
  44. 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.
  45. Dimitrios Nikolaou & Apostolos Ziakopoulos & George Yannis, 2023. "A Review of Surrogate Safety Measures Uses in Historical Crash Investigations," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
  46. Zongyuan Xia & Bo Tang & Long Qin & Huiguo Zhang & Xijian Hu, 2023. "Spatially Dependent Bayesian Modeling of Geostatistics Data and Its Application for Tuberculosis (TB) in China," Mathematics, MDPI, vol. 11(19), pages 1-15, October.
  47. Massimo Ventrucci & Daniela Cocchi & Gemma Burgazzi & Alex Laini, 2020. "PC priors for residual correlation parameters in one-factor mixed models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 745-765, December.
  48. Wang, Xudong & Cheng, Zhanhong & Trépanier, Martin & Sun, Lijun, 2021. "Modeling bike-sharing demand using a regression model with spatially varying coefficients," Journal of Transport Geography, Elsevier, vol. 93(C).
  49. Chen, Yewen & Chang, Xiaohui & Luo, Fangzhi & Huang, Hui, 2023. "Additive dynamic models for correcting numerical model outputs," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  50. Giovanna Jona Lasinio & Gianluca Mastrantonio & Alessio Pollice, 2013. "Discussing the “big n problem”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(1), pages 97-112, March.
  51. Zilber, Daniel & Katzfuss, Matthias, 2021. "Vecchia–Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  52. Kleiber, William & Nychka, Douglas, 2012. "Nonstationary modeling for multivariate spatial processes," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 76-91.
  53. Mateo, Rubén G. & Arellano, Gabriel & Gómez-Rubio, Virgilio & Tello, J. Sebastián & Fuentes, Alfredo F. & Cayola, Leslie & Loza, M. Isabel & Cala, Victoria & Macía, Manuel J., 2022. "Insights on biodiversity drivers to predict species richness in tropical forests at the local scale," Ecological Modelling, Elsevier, vol. 473(C).
  54. Joseph Guinness, 2022. "Inverses of Matérn covariances on grids [Spatial modeling with R-INLA: A review]," Biometrika, Biometrika Trust, vol. 109(2), pages 535-541.
  55. Menafoglio, Alessandra & Secchi, Piercesare, 2017. "Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics," European Journal of Operational Research, Elsevier, vol. 258(2), pages 401-410.
  56. Federico Ferraccioli & Eleonora Arnone & Livio Finos & James O. Ramsay & Laura M. Sangalli, 2021. "Nonparametric density estimation over complicated domains," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 346-368, April.
  57. Ingrid Sandvig Thorsen & Bård Støve & Hans J. Skaug, 2023. "A TMB Approach to Study Spatial Variation in Weather-Generated Claims in Insurance," SN Operations Research Forum, Springer, vol. 4(4), pages 1-27, December.
  58. Laia Maynou & Bruce Morley & Mercedes Monfort & Javier Ordóñez, 2020. "House price convergence Across Europe," Working Papers 2020/07, Economics Department, Universitat Jaume I, Castellón (Spain).
  59. 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.
  60. Nikos Tzavidis & Li‐Chun Zhang & Angela Luna & Timo Schmid & Natalia Rojas‐Perilla, 2018. "From start to finish: a framework for the production of small area official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 927-979, October.
  61. Yuheng Ling, 2020. "Time, space and hedonic prediction accuracy: evidence from Corsican apartment markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 367-388, April.
  62. Duan, Yimeng & Zhang, Shen & Yu, Zhuoran, 2021. "Applying Bayesian spatio-temporal models to demand analysis of shared bicycle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
  63. 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.
  64. Brown, Patrick E., 2015. "Model-Based Geostatistics the Easy Way," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i12).
  65. Jonathan Bradley & Noel Cressie & Tao Shi, 2015. "Comparing and selecting spatial predictors using local criteria," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 1-28, March.
  66. Christopher J. Geoga & Mihai Anitescu & Michael L. Stein, 2021. "Flexible nonstationary spatiotemporal modeling of high‐frequency monitoring data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.
  67. Zaida C. Quiroz & Marcos O. Prates & Håvard Rue, 2015. "A Bayesian approach to estimate the biomass of anchovies off the coast of Perú," Biometrics, The International Biometric Society, vol. 71(1), pages 208-217, March.
  68. Simon N. Wood, 2020. "Inference and computation with generalized additive models and their extensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 307-339, June.
  69. Matthias Katzfuss, 2017. "A Multi-Resolution Approximation for Massive Spatial Datasets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 201-214, January.
  70. Laurini, Márcio Poletti, 2017. "The spatio-temporal dynamics of ethanol/gasoline price ratio in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1-12.
  71. Karim Anaya‐Izquierdo & Neal Alexander, 2021. "Spatial regression and spillover effects in cluster randomized trials with count outcomes," Biometrics, The International Biometric Society, vol. 77(2), pages 490-505, June.
  72. 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.
  73. Taylor, Benjamin M. & Davies, Tilman M. & Rowlingson, Barry S. & Diggle, Peter J., 2015. "Bayesian Inference and Data Augmentation Schemes for Spatial, Spatiotemporal and Multivariate Log-Gaussian Cox Processes in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i07).
  74. Jonathan Rougier & Aoibheann Brady & Jonathan Bamber & Stephen Chuter & Sam Royston & Bramha Dutt Vishwakarma & Richard Westaway & Yann Ziegler, 2023. "The scope of the Kalman filter for spatio‐temporal applications in environmental science," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
  75. Coll, M. & Pennino, M. Grazia & Steenbeek, J. & Sole, J. & Bellido, J.M., 2019. "Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches," Ecological Modelling, Elsevier, vol. 405(C), pages 86-101.
  76. Ying C. MacNab, 2018. "Rejoinder on: Some recent work on multivariate Gaussian Markov random fields," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 554-569, September.
  77. Laura Serra & Claudio Detotto & Pablo Juan & Marco Vannini, 2022. "Intersectoral and spatial spill-overs of firms’ bankruptcy in Spain," Letters in Spatial and Resource Sciences, Springer, vol. 15(2), pages 197-211, August.
  78. Laura M. Sangalli & James O. Ramsay & Timothy O. Ramsay, 2013. "Spatial spline regression models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 681-703, September.
  79. Margaret R Donald & Kerrie L Mengersen & Rick R Young, 2015. "A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-22, October.
  80. Osafu Augustine Egbon & Omodolapo Somo-Aina & Ezra Gayawan, 2021. "Spatial Weighted Analysis of Malnutrition Among Children in Nigeria: A Bayesian Approach," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 495-523, December.
  81. Kleiber, William, 2016. "High resolution simulation of nonstationary Gaussian random fields," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 277-288.
  82. Athanasios C. Micheas & Jiaxun Chen, 2018. "sppmix: Poisson point process modeling using normal mixture models," Computational Statistics, Springer, vol. 33(4), pages 1767-1798, December.
  83. Laura Serra & Claudio Detotto & Marco Vannini, 2022. "Public lands as a mitigator of wildfire burned area using a spatio-temporal model applied in Sardinia," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 621-635, December.
  84. Peter A. Gao & Jonathan Wakefield, 2023. "A Spatial Variance‐Smoothing Area Level Model for Small Area Estimation of Demographic Rates," International Statistical Review, International Statistical Institute, vol. 91(3), pages 493-510, December.
  85. Jialuo Liu & Tingjin Chu & Jun Zhu & Haonan Wang, 2022. "Large spatial data modeling and analysis: A Krylov subspace approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1115-1143, September.
  86. Vanhatalo, Jarno & Veneranta, Lari & Hudd, Richard, 2012. "Species distribution modeling with Gaussian processes: A case study with the youngest stages of sea spawning whitefish (Coregonus lavaretus L. s.l.) larvae," Ecological Modelling, Elsevier, vol. 228(C), pages 49-58.
  87. Angela Ferretti & L. Ippoliti & P. Valentini & R. J. Bhansali, 2023. "Long memory conditional random fields on regular lattices," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
  88. 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.
  89. Dong Liang & Genevieve Nesslage & Michael Wilberg & Thomas Miller, 2017. "Bayesian Calibration of Blue Crab (Callinectes sapidus) Abundance Indices Based on Probability Surveys," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 481-497, December.
  90. Andreia Monteiro & Raquel Menezes & Maria Eduarda Silva, 2021. "Modelling informative time points: an evolutionary process approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 364-382, June.
  91. Huang, Chunfeng & Li, Ao, 2021. "On Lévy’s Brownian motion and white noise space on the circle," Statistics & Probability Letters, Elsevier, vol. 171(C).
  92. 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.
  93. Yi Liu & Gavin Shaddick & James V. Zidek, 2017. "Incorporating High-Dimensional Exposure Modelling into Studies of Air Pollution and Health," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 559-581, December.
  94. Sigrist, Fabio & Künsch, Hans R. & Stahel, Werner A., 2015. "spate: An R Package for Spatio-Temporal Modeling with a Stochastic Advection-Diffusion Process," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i14).
  95. Francesca Della Rocca & Pietro Milanesi, 2022. "The New Dominator of the World: Modeling the Global Distribution of the Japanese Beetle under Land Use and Climate Change Scenarios," Land, MDPI, vol. 11(4), pages 1-17, April.
  96. Giri Gopalan & Birgir Hrafnkelsson & Christopher K. Wikle & Håvard Rue & Guðfinna Aðalgeirsdóttir & Alexander H. Jarosch & Finnur Pálsson, 2019. "A Hierarchical Spatiotemporal Statistical Model Motivated by Glaciology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(4), pages 669-692, December.
  97. 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.
  98. Laia Maynou & Marc Saez & Jordi Bacaria & Guillem Lopez-Casasnovas, 2015. "Health inequalities in the European Union: an empirical analysis of the dynamics of regional differences," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(5), pages 543-559, June.
  99. Bevilacqua, Moreno & Caamaño-Carrillo, Christian & Porcu, Emilio, 2022. "Unifying compactly supported and Matérn covariance functions in spatial statistics," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  100. Marc Francke & Alex Van de Minne, 2021. "Modeling unobserved heterogeneity in hedonic price models," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(4), pages 1315-1339, December.
  101. Xu Ning & Francis K. C. Hui & Alan H. Welsh, 2023. "A double fixed rank kriging approach to spatial regression models with covariate measurement error," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
  102. Xiaoyu Xiong & Benjamin D. Youngman & Theodoros Economou, 2021. "Data fusion with Gaussian processes for estimation of environmental hazard events," Environmetrics, John Wiley & Sons, Ltd., vol. 32(3), May.
  103. Creasey Peter E. & Lang Annika, 2018. "Fast generation of isotropic Gaussian random fields on the sphere," Monte Carlo Methods and Applications, De Gruyter, vol. 24(1), pages 1-11, March.
  104. Joshua L. Warren & Penny Gordon‐Larsen, 2018. "Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 783-802, June.
  105. 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.
  106. Raphaël de Fondeville & Anthony C. Davison, 2022. "Functional peaks‐over‐threshold analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1392-1422, September.
  107. Matthew J. Heaton & Abhirup Datta & Andrew O. Finley & Reinhard Furrer & Joseph Guinness & Rajarshi Guhaniyogi & Florian Gerber & Robert B. Gramacy & Dorit Hammerling & Matthias Katzfuss & Finn Lindgr, 2019. "A Case Study Competition Among Methods for Analyzing Large Spatial Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 398-425, September.
  108. Edwards, Matthew & Castruccio, Stefano & Hammerling, Dorit, 2020. "Marginally parameterized spatio-temporal models and stepwise maximum likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
  109. 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.
  110. Morgan Kelly, 2020. "Direct Standard Errors for Regressions with Spatially Autocorrelated Residuals," Working Papers 202006, School of Economics, University College Dublin.
  111. David Bolin, 2014. "Spatial Matérn Fields Driven by Non-Gaussian Noise," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 557-579, September.
  112. Yuan Yan & Eva Cantoni & Chris Field & Margaret Treble & Joanna Mills Flemming, 2023. "Spatiotemporal modeling of mature‐at‐length data using a sliding window approach," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
  113. Peter J. Diggle & Emanuele Giorgi, 2016. "Model-Based Geostatistics for Prevalence Mapping in Low-Resource Settings," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1096-1120, July.
  114. Sameh Abdulah & Yuxiao Li & Jian Cao & Hatem Ltaief & David E. Keyes & Marc G. Genton & Ying Sun, 2023. "Large‐scale environmental data science with ExaGeoStatR," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
  115. 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).
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