Anisotropy models for spatial data

DOI10.1007/s11004-015-9594-xzbMath1397.86020OpenAlexW1983218172MaRDI QIDQ1789180

Rachid Senoussi, Emilio Porcu, Denis Allard

Publication date: 10 October 2018

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-015-9594-x

zbMATH Keywords

spatial statisticsvariogramisotropycovarianceturning band method

Mathematics Subject Classification ID

Random fields (60G60) Inference from spatial processes (62M30) Anisotropy in solid mechanics (74E10) Geostatistics (86A32)

Related Items (max. 100)

Multivariate Gaussian Random Fields over Generalized Product Spaces involving the Hypertorus ⋮ On Some Characteristics of Gaussian Covariance Functions ⋮ Fast and exact synthesis of some operator scaling Gaussian random fields ⋮ On critical points of Gaussian random fields under diffeomorphic transformations ⋮ Identification and isotropy characterization of deformed random fields through excursion sets ⋮ Unnamed Item ⋮ Estimation of local anisotropy based on level sets

Uses Software

• RandomFields

Cites Work

• Unnamed Item
• Unnamed Item
• Objective Bayesian analysis of geometrically anisotropic spatial data
• From Schoenberg to Pick-Nevanlinna: toward a complete picture of the variogram class
• Interpolation of spatial data. Some theory for kriging
• On a class of space-time intrinsic random functions
• Analogies and correspondences between variograms and covariance functions
• Geostatistics
• Why is isotropy so prevalent in spatial statistics?
• Fractal Analysis of Surface Roughness by Using Spatial Data
• Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach
• Dimension walks and Schoenberg spectral measures
• Closed form solutions of the two-dimensional turning bands equation

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