论文信息 - Conditioning of the stationary kriging matrices for some well-known covariance models

Conditioning of the stationary kriging matrices for some well-known covariance models

In this paper, the condition number of the stationary kriging matrix is studied for some well-known covariance models. Indeed, the robustness of the kriging weights is strongly affected by this measure. Such an analysis can justify the choice of a covariance function among other admissible models which could fit a given experimental covariance equally well.

D. Posa

[1] Åke Björck,et al. Numerical Methods , 2021, Markov Renewal and Piecewise Deterministic Processes.

[2] P. J. Huber. Robust Statistical Procedures , 1977 .

[3] N. Cressie,et al. Robust estimation of the variogram: I , 1980 .

[4] T. H. Starks,et al. The effect of drift on the experimental semivariogram , 1982 .

[5] Peter K. Kitanidis,et al. Statistical estimation of polynomial generalized covariance functions and hydrologic applications , 1983 .

[6] Phil Diamond,et al. Robustness of variograms and conditioning of kriging matrices , 1984 .

[7] M. Armstrong. Common problems seen in variograms , 1984 .

[8] F. Graybill,et al. Matrices with Applications in Statistics. , 1984 .

[9] Margaret Armstrong,et al. Improving the Estimation and Modelling of the Variogram , 1984 .

[10] G. Christakos. On the Problem of Permissible Covariance and Variogram Models , 1984 .

[11] A. Bárdossy. Notes on the robustness of the kriging system , 1988 .