Results 171 to 180 of about 26,023 (245)
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Variance–Covariance Matrix of the Experimental Variogram: Assessing Variogram Uncertainty
Mathematical Geology, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pardo-Iguzquiza, E., Dowd, P.
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Highly Robust Variogram Estimation
Mathematical Geology, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Estimating Variogram Uncertainty
Mathematical Geology, 2004The variogram is central to any geostatistical survey, but the precision of a variogram estimated from sample data by the method of moments is unknown. It is important to be able to quantify variogram uncertainty to ensure that the variogram estimate is sufficiently accurate for kriging.
B. P. Marchant, R. M. Lark
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Chromatin pattern by variogram analysis
Microscopy Research and Technique, 1997Many cytological processes such as cell proliferation, differentiation, transformation, apoptosis, etc., are accompanied by specific chromatin changes, usually identified on the basis of the relative content of euchromatin and heterochromatin. In order to achieve a quantitative, non-subjective evaluation of the chromatin pattern, two different ...
DIAZ, GIACOMO +3 more
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Bulletin of Engineering Geology and the Environment, 2021
P. Kulatilake +7 more
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P. Kulatilake +7 more
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On nonparametric variogram estimation
Journal of the Korean Statistical Society, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Tae Yoon, Park, Jeong-Soo
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Trimmed Spatio-Temporal Variogram Estimator
2022The spatio-temporal variogram is the key element in spatiotemporal prediction based on kriging, but the classical estimator of this parameter is very sensitive to outliers. In this contributed paper we propose a trimmed estimator of the spatio-temporal variogram as a robust estimator.
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Cross-Validation and Variogram Estimation
Theory of Probability & Its Applications, 1993One of the methods used for the interpolation of spatially correlated data is known as kriging, which is a regression technique. Consider a model of the form \(Z(x)\), a random function defined in \(p\)-dimensional space satisfying a weak stationarity condition as follows: \[ \begin{aligned} & E[Z(x + h) - Z(x)] = 0 \text{ for all } x, h;\tag\text{i}\\
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Calculation of Uncertainty in the Variogram
Mathematical Geology, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ortiz C., Julián, Deutsch, Clayton V.
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