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Discussion of “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach” by Huang Huang, Stefano Castruccio, Allison H. Baker and Marc Genton

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  • Sudipto Banerjee

    (UCLA Department of Biostatistics)

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  • Sudipto Banerjee, 2023. "Discussion of “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach” by Huang Huang, Stefano Castruccio, Allison H. Baker and Marc Genton," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 365-369, June.
    • Handle: RePEc:spr:jagbes:v:28:y:2023:i:2:d:10.1007_s13253-023-00541-6
    DOI: 10.1007/s13253-023-00541-6
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    References listed on IDEAS

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    1. Gramacy, Robert B., 2016. "laGP: Large-Scale Spatial Modeling via Local Approximate Gaussian Processes in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i01).
    2. Christopher Wikle & Mevin Hooten, 2010. "Rejoinder on: A general science-based framework for dynamical spatio-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 466-468, November.
    3. Higdon, Dave & Gattiker, James & Williams, Brian & Rightley, Maria, 2008. "Computer Model Calibration Using High-Dimensional Output," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 570-583, June.
    4. Marc C. Kennedy & Anthony O'Hagan, 2001. "Bayesian calibration of computer models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(3), pages 425-464.
    5. Matthias Katzfuss & Jonathan R. Stroud & Christopher K. Wikle, 2020. "Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 866-885, April.
    6. Christopher Wikle & Mevin Hooten, 2010. "A general science-based framework for dynamical spatio-temporal models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 417-451, November.
    7. Lu Zhang & Sudipto Banerjee, 2022. "Spatial factor modeling: A Bayesian matrix‐normal approach for misaligned data," Biometrics, The International Biometric Society, vol. 78(2), pages 560-573, June.
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