论文信息 - Generalized covariance functions in estimation

Generalized covariance functions in estimation

I discuss the role of generalized covariance functions in best linear unbiased estimation and methods for their selection. It is shown that the experimental variogram (or covariance function) of the detrended data can be used to obtain a preliminary estimate of the generalized covariance function without iterations and I discuss the advantages of other parameter estimation methods.

P. Kitanidis

[1] G. Matheron. The intrinsic random functions and their applications , 1973, Advances in Applied Probability.

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

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

[4] Margaret Armstrong,et al. Problems with universal kriging , 1984 .

[5] P. Kitanidis,et al. An Application of the Geostatistical Approach to the Inverse Problem in Two-Dimensional Groundwater Modeling , 1984 .

[6] Andre G. Journel,et al. Geostatistics: Models and tools for the earth sciences , 1986 .

[7] Peter K. Kitanidis,et al. PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES , 1987 .

[8] Ronald Christensen,et al. The equivalence of predictions from universal kriging and intrinsic random-function kriging , 1990 .

[9] Peter K. Kitanidis,et al. Orthonormal residuals in geostatistics: Model criticism and parameter estimation , 1991 .