Results 171 to 180 of about 9,440 (213)
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Stochastic simulation of semivariograms
Journal of the International Association for Mathematical Geology, 1982The semivariogram obtained from simulated space series formed by an autoregressive (AR) process gives a ready explanation for most of the common types. Linear semivariograms arise from a random walk (Brownian motion) process while the transitive and exponential types are generated by an AR process of first order. The continuous (“Gaussian”) type arises
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Using Semivariogram Parameter Uncertainty in Hydrogeological Applications
Groundwater, 2009Abstract Geostatistical estimation (kriging) and geostatistical simulation are routinely used in ground water hydrology for optimal spatial interpolation and Monte Carlo risk assessment, respectively. Both techniques are based on a model of spatial variability (semivariogram or covariance) that generally is not known but must be ...
Eulogio, Pardo-Igúzquiza +3 more
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Thermal Evaluation to Identify Nodules Using Semivariogram Curves
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Thermography can contribute to the early diagnosis of tumors by identifying nodules that need to be analyzed. The objective of this paper was to verify possible semivariogram curves to identify the possible spatial behavior centered in the region with the nodule and capture the thermal behavioral information surroundings of this point.
Camila Gabriela Grassmann +3 more
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A new class of semiparametric semivariogram and nugget estimators
Computational Statistics & Data Analysis, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patrick S. Carmack +5 more
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The semivariogram in remote sensing: An introduction
Remote Sensing of Environment, 1988Abstract The Earth's surface and remotely sensed imagery contain spatial information that, if quantified, could be used to optimize many sampling procedures in remote sensing. Until recently a suitable and simple technique for the spatial characterisation of surfaces was not readily available.
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Journal of environmental sciences (China), 2002
The spatial variation of soil nutrients in topsoil (0-20 cm) was analyzed using semivariogram in the Zunhua County of Hebei Province, China. The effect on semivariogram with randomly deleted data and kriged estimates using various reduced sample sizes was also analyzed.
X D, Guo, B J, Fu, K M, Ma, L D, Chen
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The spatial variation of soil nutrients in topsoil (0-20 cm) was analyzed using semivariogram in the Zunhua County of Hebei Province, China. The effect on semivariogram with randomly deleted data and kriged estimates using various reduced sample sizes was also analyzed.
X D, Guo, B J, Fu, K M, Ma, L D, Chen
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A Composite Likelihood Approach to Semivariogram Estimation
Journal of Agricultural, Biological, and Environmental Statistics, 1999This article proposes the use of estimating functions based on composite likelihood for the estimation of isotropic as well as geometrically anisotropic semivariogram parameters. The composite likelihood approach is objective, eliminating the specification of distance lags and lag tolerances associated with the commonly used moment estimator ...
Frank C. Curriero, Subhash Lele
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Semivariogram Models Based on Geometric Offsets
Mathematical Geology, 2006Kriging-based geostatistical models require a semivariogram model. Next to the initial decision of stationarity, the choice of an appropriate semivariogram model is the most important decision in a geostatistical study. Common practice consists of fitting experimental semivariograms with a nested combination of proven models such as the spherical ...
Michael J. Pyrcz, Clayton V. Deutsch
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The Effects of Influential Observations on Sample Semivariograms
Journal of Agricultural, Biological, and Environmental Statistics, 1997Optimal prediction of the values of regionalized variables or the means of random fields is often accomplished by using kriging methods. These methods rely on satisfactory estimation of the underlying spatial semivariograms and the fitting of semivariogram models.
Sabyasachi Basu +3 more
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Asymptotic normality of the Nadaraya–Watson semivariogram estimators
TEST, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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