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Approximating likelihoods for large spatial data sets

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Cited by:

  1. Sudipto Banerjee & Alan E. Gelfand & Andrew O. Finley & Huiyan Sang, 2008. "Gaussian predictive process models for large spatial data sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 825-848, September.
  2. Huang, Whitney K. & Chung, Yu-Min & Wang, Yu-Bo & Mandel, Jeff E. & Wu, Hau-Tieng, 2022. "Airflow recovery from thoracic and abdominal movements using synchrosqueezing transform and locally stationary Gaussian process regression," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  3. Yasumasa Matsuda & Yoshihiro Yajima, 2009. "Fourier analysis of irregularly spaced data on Rd," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 191-217, January.
  4. 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).
  5. Jun, Mikyoung, 2014. "Matérn-based nonstationary cross-covariance models for global processes," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 134-146.
  6. Magnussen, Steen & Reeves, Rob, 2008. "A method for bias-reduction of sample-based MLE of the autologistic model," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 103-111, September.
  7. 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.
  8. 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.
  9. Elsa Vazquez & Jeffrey R. Wilson, 2021. "Partitioned method of valid moment marginal model with Bayes interval estimates for correlated binary data with time-dependent covariates," Computational Statistics, Springer, vol. 36(4), pages 2701-2718, December.
  10. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
  11. 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.
  12. Zheng, Xueying & Xue, Lan & Qu, Annie, 2018. "Time-varying correlation structure estimation and local-feature detection for spatio-temporal data," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 221-239.
  13. Moreno Bevilacqua & Alfredo Alegria & Daira Velandia & Emilio Porcu, 2016. "Composite Likelihood Inference for Multivariate Gaussian Random Fields," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 448-469, September.
  14. Delgado, Miguel A. & Robinson, Peter M., 2015. "Non-nested testing of spatial correlation," Journal of Econometrics, Elsevier, vol. 187(1), pages 385-401.
  15. Daniels, M.J. & Pourahmadi, M., 2009. "Modeling covariance matrices via partial autocorrelations," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2352-2363, November.
  16. 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.
  17. Erhardt, Tobias Michael & Czado, Claudia & Schepsmeier, Ulf, 2015. "Spatial composite likelihood inference using local C-vines," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 74-88.
  18. 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).
  19. Chen, Kun & Chan, Ngai Hang & Yau, Chun Yip & Hu, Jie, 2023. "Penalized Whittle likelihood for spatial data," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
  20. 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.
  21. Guhaniyogi, Rajarshi & Banerjee, Sudipto, 2019. "Multivariate spatial meta kriging," Statistics & Probability Letters, Elsevier, vol. 144(C), pages 3-8.
  22. 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.
  23. Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  24. Lucia Paci & Alan E. Gelfand & and María Asunción Beamonte & Pilar Gargallo & Manuel Salvador, 2020. "Spatial hedonic modelling adjusted for preferential sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 169-192, January.
  25. M. Bevilacqua & A. Fassò & C. Gaetan & E. Porcu & D. Velandia, 2016. "Covariance tapering for multivariate Gaussian random fields estimation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 21-37, March.
  26. Padoan, Simone A. & Bevilacqua, Moreno, 2015. "Analysis of Random Fields Using CompRandFld," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i09).
  27. Lu Zhang & Sudipto Banerjee & Andrew O. Finley, 2021. "High‐dimensional multivariate geostatistics: A Bayesian matrix‐normal approach," Environmetrics, John Wiley & Sons, Ltd., vol. 32(4), June.
  28. Schmidt, Paul & Mühlau, Mark & Schmid, Volker, 2017. "Fitting large-scale structured additive regression models using Krylov subspace methods," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 59-75.
  29. Yan Chen & Youran Qi & Qing Liu & Peter Chien, 2018. "Sequential sampling enhanced composite likelihood approach to estimation of social intercorrelations in large-scale networks," Quantitative Marketing and Economics (QME), Springer, vol. 16(4), pages 409-440, December.
  30. Litvinenko, Alexander & Sun, Ying & Genton, Marc G. & Keyes, David E., 2019. "Likelihood approximation with hierarchical matrices for large spatial datasets," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 115-132.
  31. Coube-Sisqueille, Sébastien & Liquet, Benoît, 2022. "Improving performances of MCMC for Nearest Neighbor Gaussian Process models with full data augmentation," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  32. repec:jss:jstsof:19:i02 is not listed on IDEAS
  33. 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.
  34. Sutradhar, Brajendra C., 2021. "Block-band behavior of spatial correlations: An analytical asymptotic study in a spatial exponential family data setup," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
  35. Paciorek, Christopher J., 2007. "Bayesian Smoothing with Gaussian Processes Using Fourier Basis Functions in the spectralGP Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 19(i02).
  36. Andrew O. Finley & Sudipto Banerjee & Patrik Waldmann & Tore Ericsson, 2009. "Hierarchical Spatial Modeling of Additive and Dominance Genetic Variance for Large Spatial Trial Datasets," Biometrics, The International Biometric Society, vol. 65(2), pages 441-451, June.
  37. Patrick R. Conrad & Youssef M. Marzouk & Natesh S. Pillai & Aaron Smith, 2016. "Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1591-1607, October.
  38. repec:cep:stiecm:/2013/568 is not listed on IDEAS
  39. Arthur P. Guillaumin & Adam M. Sykulski & Sofia C. Olhede & Frederik J. Simons, 2022. "The Debiased Spatial Whittle likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1526-1557, September.
  40. Bledar A. Konomi & Emily L. Kang & Ayat Almomani & Jonathan Hobbs, 2023. "Bayesian Latent Variable Co-kriging Model in Remote Sensing for Quality Flagged Observations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 423-441, September.
  41. Eidsvik, Jo & Finley, Andrew O. & Banerjee, Sudipto & Rue, Håvard, 2012. "Approximate Bayesian inference for large spatial datasets using predictive process models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1362-1380.
  42. Caragea, Petruta C. & Smith, Richard L., 2007. "Asymptotic properties of computationally efficient alternative estimators for a class of multivariate normal models," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1417-1440, August.
  43. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.
  44. Bachoc, François & Bevilacqua, Moreno & Velandia, Daira, 2019. "Composite likelihood estimation for a Gaussian process under fixed domain asymptotics," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
  45. Zahra Barzegar & Firoozeh Rivaz, 2020. "A scalable Bayesian nonparametric model for large spatio-temporal data," Computational Statistics, Springer, vol. 35(1), pages 153-173, March.
  46. Furrer, Reinhard & Bachoc, François & Du, Juan, 2016. "Asymptotic properties of multivariate tapering for estimation and prediction," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 177-191.
  47. Karl Pazdernik & Ranjan Maitra & Douglas Nychka & Stephan Sain, 2018. "Reduced Basis Kriging for Big Spatial Fields," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 280-300, August.
  48. Yasumasa Matsuda, 2013. "Generalized Whittle Estimate For Nonstationary Spatial Data," TERG Discussion Papers 305, Graduate School of Economics and Management, Tohoku University.
  49. Ryan J. Parker & Brian J. Reich & Jo Eidsvik, 2016. "A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 569-587, September.
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