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Discussion of “Saving storage in climate ensembles: a model-based stochastic approach”. (English) Zbl 07749316

Discussion on [H. Huang et al., ibid. 28, No. 2, 324–344 (2023; Zbl 07749311)].

MSC:

62P12 Applications of statistics to environmental and related topics

Citations:

Zbl 07749311

Software:

laGP; CAM3
Full Text: DOI

References:

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[2] Collins WD, Rasch PJ, Boville BA, Hack JJ, McCaa JR, Williamson DL, Kiehl JT, Briegleb B (2004) Description of the NCAR Community Atmosphere Model (CAM 3.0). Technical Report TN-464+STR, National Center for Atmorspheric Research. https://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf
[3] Datta, A.; Banerjee, S.; Finley, AO; Hamm, NAS; Schaap, M., Non-separable dynamic nearest-neighbor gaussian process models for large spatio-temporal data with an application to particulate matter analysis, Ann Appl Stat, 10, 1286-1316 (2016) · Zbl 1391.62269 · doi:10.1214/16-AOAS931
[4] Frankenburg I, Banerjee S (2022) Dynamic Bayesian learning and calibration of spatiotemporal mechanistic systems. arXiv: 2208.06528v2
[5] Genton MG, Kleiber W (2015) Cross-covariance functions for multivariate geostatistics. Stat Sci, 147-163 · Zbl 1332.86010
[6] Gramacy, R., laGP: large-scale spatial modeling via local approximate gaussian processes in R, J Stat Softw, 72, 1, 1-46 (2016) · doi:10.18637/jss.v072.i01
[7] Gramacy, RB; Haaland, B., Speeding up neighborhood search in local Gaussian process prediction, Technometrics, 58, 3, 294-303 (2016) · doi:10.1080/00401706.2015.1027067
[8] Gramacy RB, Niemi J, Weiss RM (2014) Massively parallel approximate Gaussian process regression. arxiv:1310.5182 · Zbl 1308.62159
[9] Higdon, D.; Gattiker, J.; Williams, B.; Rightley, M., Computer model calibration using high-dimensional output, J Am Stat Assoc, 103, 482, 570-583 (2008) · Zbl 1469.62414 · doi:10.1198/016214507000000888
[10] Katzfuss, M.; Stroud, JR; Wikle, CK, Ensemble Kalman methods for high-dimensional hierarchical dynamic space-time models, J Am Stat Assoc, 115, 530, 866-885 (2020) · Zbl 1445.62246 · doi:10.1080/01621459.2019.1592753
[11] Kennedy, MC; O’Hagan, A., Bayesian calibration of computer models, J R Stat Soc Series B Stat Methodol, 63, 3, 425-464 (2001) · Zbl 1007.62021 · doi:10.1111/1467-9868.00294
[12] Monteiro, JVD; Banerjee, S.; Ramachandran, G., Bayesian modeling for physical processes in industrial hygiene using misaligned workplace data, Technometrics, 56, 2, 238-247 (2014) · doi:10.1080/00401706.2013.836988
[13] Wikle, CK; Hooten, MB, A general science-based framework for dynamical spatio-temporal models, TEST, 19, 3, 417-451 (2010) · Zbl 1203.37141 · doi:10.1007/s11749-010-0209-z
[14] Zhang, L.; Banerjee, S., Spatial factor modeling: a Bayesian matrix-normal approach for misaligned data, Biometrics, 78, 2, 560-573 (2022) · Zbl 1520.62400 · doi:10.1111/biom.13452
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