Geostatistical Modelling Using Non‐Gaussian Matérn Fields
By Jonas Wallin, David Bolin. 2015
82 citations recorded by the source corpus.
Subfields: Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/d80f1653c23228b1460e79350e3d330f8a26dc1f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Daniel P. Simpson
- Finn Lindgren
- Håvard Rue
- Andrea Riebler
- David Bolin
- Geir-Arne Fuglstad
- H. Bakka
- Elias Teixeira Krainski
In Global and Planetary Change
- Daniel P. Simpson
- Håvard Rue
- Geir-Arne Fuglstad
- Lassi Roininen
- Mark A. Girolami
- M. Markkanen
- Sari Lasanen
- David Bolin
Citations in the corpus
- Hyperpriors for Matérn fields with applications in Bayesian inversion (2016, methodology): “Hence, [40] provides an interesting example on hierarchical construction with non-Gaussian structures.”
- Spatial modelling with R-INLA: A review (2018, methodology): “The model that is used for the simulation is where M is normal inverse Gaussian (NIG) noise, see Wallin and Bolin (2015) for a formal definition.”