Title: | A Hierarchical Spatiotemporal Statistical Model Motivated by Glaciology |
Author: |
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Date: | 2019-06-12 |
Language: | English |
Scope: | 669-692 |
University/Institute: | Háskóli Íslands University of Iceland |
School: | Verkfræði- og náttúruvísindasvið (HÍ) School of Engineering and Natural Sciences (UI) |
Department: | Raunvísindadeild (HÍ) Faculty of Physical Sciences (UI) Jarðvísindadeild (HÍ) Faculty of Earth Sciences (UI) |
Series: | Journal of Agricultural, Biological and Environmental Statistics;24(4) |
ISSN: | 1085-7117 1537-2693 (eISSN) |
DOI: | 10.1007/s13253-019-00367-1 |
Subject: | Model discrepancy; Uncertainty quantification; Emulation; Reiknilíkön; Jöklafræði |
URI: | https://hdl.handle.net/20.500.11815/1949 |
Citation:Gopalan, G., Hrafnkelsson, B., Wikle, C.K. et al. A Hierarchical Spatiotemporal Statistical Model Motivated by Glaciology. JABES 24, 669–692 (2019). https://doi.org/10.1007/s13253-019-00367-1
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Abstract:In this paper, we extend and analyze a Bayesian hierarchical spatiotemporal model for physical systems. A novelty is to model the discrepancy between the output of a computer simulator for a physical process and the actual process values with a multivariate random walk. For computational efficiency, linear algebra for bandwidth limited matrices is utilized, and first-order emulator inference allows for the fast emulation of a numerical partial differential equation (PDE) solver. A test scenario from a physical system motivated by glaciology is used to examine the speed and accuracy of the computational methods used, in addition to the viability of modeling assumptions. We conclude by discussing how the model and associated methodology can be applied in other physical contexts besides glaciology.
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Description:This is a post-peer-review, pre-copyedit version of an article published in Journal of Agricultural, Biological and Environmental Statistics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s13253-019-00367-1
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