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Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes

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  • Andrew Finley
  • Sudipto Banerjee
  • Alan Gelfand

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  • Andrew Finley & Sudipto Banerjee & Alan Gelfand, 2012. "Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes," Journal of Geographical Systems, Springer, vol. 14(1), pages 29-47, January.
    • Handle: RePEc:kap:jgeosy:v:14:y:2012:i:1:p:29-47
    DOI: 10.1007/s10109-011-0154-8
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    References listed on IDEAS

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    1. R. Pace & James LeSage, 2009. "A sampling approach to estimate the log determinant used in spatial likelihood problems," Journal of Geographical Systems, Springer, vol. 11(3), pages 209-225, September.
    2. Fuentes, Montserrat, 2007. "Approximate Likelihood for Large Irregularly Spaced Spatial Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 321-331, March.
    3. Crainiceanu, Ciprian M. & Diggle, Peter J. & Rowlingson, Barry, 2008. "Bivariate Binomial Spatial Modeling of Loa loa Prevalence in Tropical Africa," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 21-37, March.
    4. Jonathan R. Stroud & Peter Müller & Bruno Sansó, 2001. "Dynamic models for spatiotemporal data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 673-689.
    5. Smith, Richard L. & Tebaldi, Claudia & Nychka, Doug & Mearns, Linda O., 2009. "Bayesian Modeling of Uncertainty in Ensembles of Climate Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 97-116.
    6. Kaufman, Cari G. & Schervish, Mark J. & Nychka, Douglas W., 2008. "Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1545-1555.
    7. Finley, Andrew O. & Sang, Huiyan & Banerjee, Sudipto & Gelfand, Alan E., 2009. "Improving the performance of predictive process modeling for large datasets," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2873-2884, June.
    8. Noel Cressie & Gardar Johannesson, 2008. "Fixed rank kriging for very large spatial data sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 209-226, February.
    9. E. E. Kammann & M. P. Wand, 2003. "Geoadditive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 1-18, January.
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    Citations

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    Cited by:

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    2. 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).
    3. Joshua S. North & Erin M. Schliep & Christopher K. Wikle, 2021. "On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi‐annual harmonics," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
    4. 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.
    5. Ting Fung Ma & Fangfang Wang & Jun Zhu & Anthony R. Ives & Katarzyna E. Lewińska, 2023. "Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 279-298, June.
    6. Finley, Andrew O. & Banerjee, Sudipto & Gelfand, Alan E., 2015. "spBayes for Large Univariate and Multivariate Point-Referenced Spatio-Temporal Data Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i13).
    7. 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.
    8. Ying Liu & Dootika Vats & James M. Flegal, 2022. "Batch Size Selection for Variance Estimators in MCMC," Methodology and Computing in Applied Probability, Springer, vol. 24(1), pages 65-93, March.

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