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Gaussian Markov Random Fields
Abstract
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studie
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Cited by
Rue, H., Martino, S., & Chopin, N. (2009) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2008.00700.x · Cited by 5,279
Self-citationLindgren, F., Rue, H., & Lindström, J. (2011) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2011.00777.x · Cited by 2,708
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Zhu, X., & Ramanan, D. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248014 · Cited by 2,120
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NCD Risk Factor Collaboration (NCD-RisC) (2016) · eLife · doi:10.7554/elife.13410 · Cited by 1,558
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Msemburi, W., Karlinsky, A., Knutson, V., Aleshin-Guendel, S., Chatterji, S., & Wakefield, J. (2023) · Nature · doi:10.1038/s41586-022-05522-2 · Cited by 1,064
Metadata
- Authors
- Rue, H., & Held, L.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2005-02-18
- OpenAlex
- W143236119
- Cited by
- 1,823
- References
- 0
- FWCI
- 26.97
- Type
- book
- Language
- en
- Open access
- closed
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