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Automatic variogram model fitting of a variogram map based on the Fourier integral method
Computational Geosciences, 2021PauloR.M. Carvalho, J. Costa
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Variogram Roughness Method for Casting Surface Characterization
International Journal of Metals, 2020D. Schimpf, F. Peters
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Fast variogram computation with FFT
Computers & Geosciences, 1996Abstract Two programs are presented to compute direct- and cross-variograms, direct and cross-covariograms, and pseudo-cross-variograms. The programs are written in MATLAB and are based on the Fast Fourier Transform algorithm (FFT). The programs accept complete, or incomplete, regular grid data.
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2009
Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of a continuous spatial process at unobserved locations given the value of the process at a set of known locations. Spatial prediction of this sort is typically performed using the method known as kriging, which provides estimates that are optimized over ...
Calder, Catherine, Cressie, Noel A
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Geostatistics is a popular class of statistical methods for estimating, or predicting, the value of a continuous spatial process at unobserved locations given the value of the process at a set of known locations. Spatial prediction of this sort is typically performed using the method known as kriging, which provides estimates that are optimized over ...
Calder, Catherine, Cressie, Noel A
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Probabilistic estimation of cross-variogram based on Bayesian inference
, 2020Jiabao Xu +5 more
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Spatial Breakdown Point of Variogram Estimators
Mathematical Geology, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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1995
The multivariate regionalization of a set of random functions can be represented with a spatial multivariate linear model. The associated multivariate nested variogram model is easily fitted to the multivariate data. Several coregionalization matrices describing the multivariate correlation structure at different scales of a phenomenon result from the ...
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The multivariate regionalization of a set of random functions can be represented with a spatial multivariate linear model. The associated multivariate nested variogram model is easily fitted to the multivariate data. Several coregionalization matrices describing the multivariate correlation structure at different scales of a phenomenon result from the ...
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Three dimensional variogram modeling and Kriging
2020In this research, semi-variograms of different directions, are used to form a three-dimensional variogram surface. A simple and practical surface generation technique, namely bilinear surface fitting method is used for this purpose. Co-variance between any of two sample points (drill holes) can be found on the surface easily. Angle and distance between
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