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Geostatistical Mode...
Geostatistical Modelling Using Non-Gaussian Matern Fields
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- Wallin, Jonas, 1981 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology
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- Bolin, David, 1983 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematisk statistik,Department of Mathematical Sciences, Mathematical Statistics,Chalmers tekniska högskola,Chalmers University of Technology,University of Gothenburg
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(creator_code:org_t)
- 2015-02-23
- 2015
- Engelska.
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Ingår i: Scandinavian Journal of Statistics. - : Wiley. - 0303-6898 .- 1467-9469. ; 42:3, s. 872-890
- Relaterad länk:
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http://dx.doi.org/10...
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Abstract
Ämnesord
Stäng
- This work provides a class of non-Gaussian spatial Matern fields which are useful for analysing geostatistical data. The models are constructed as solutions to stochastic partial differential equations driven by generalized hyperbolic noise and are incorporated in a standard geostatistical setting with irregularly spaced observations, measurement errors and covariates. A maximum likelihood estimation technique based on the Monte Carlo expectation-maximization algorithm is presented, and a Monte Carlo method for spatial prediction is derived. Finally, an application to precipitation data is presented, and the performance of the non-Gaussian models is compared with standard Gaussian and transformed Gaussian models through cross-validation.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Laplace
- Markov random fields
- Matern covariances
- MCEM algorithm
- normal inverse Gaussian
- SPDE
- variance Gamma
- Matern covariances
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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