Abstract
The criterion used to select infill sample locations should depend on the sampling objective. Minimizing the global estimation variance is the most widely used criterion and is suitable for many problems. However, when the objective of the sampling program is to partition an area of interest into zones of high values and zones of low values, minimizing the expected cost of classification errors is a more appropriate criterion. Unlike the global estimation variance, the cost of classification errors incorporates both the sample locations and the sample values into an objective infill-sampling design criterion.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anderson, T. W., 1958, An Introduction to Multivariate Statistical Analysis: John Wiley & Sons, New York, 374 p.
Barnes, R. J., 1986, The Cost of Risk and the Value of Information in Mine Planning: Proceedings of the 19th APCOM Symposium, Society of Mining Engineers, New York, p. 459–469.
Barnes, R. J., 1988, Sample Design for Geologic Site Characterization: Presented at the 3rd International Geostatistical Congress, Avignon, France, September 1988.
Bras, R. L., and Rodriguez-Iturbe, I., 1985, Random Functions and Hydrology: Addison-Wesley, Reading, Massachusetts, 559 p.
Chou, D., and Schenk, D. E., 1984, Selecting Optimum Drilling Locations by Groups: Society of Mining Engineers preprint 84–62.
Davis, D. R., and Dvoranchik, W. M., 1971, Evaluation of the Worth of Additional Data: Water Resour. Res., v. 7, p. 700–707.
Davis, D. R., Duckstein, L., and Krzysztofowicz, R., 1979, The Worth of Hydrologic Data for Nonoptimal Decision Making: Water Resour. Res., v. 15, p. 1733–1742.
Dawdy, D. R., 1979, The Worth of Hydrologic Data: Water Resour. Res. v. 15, p. 1726–1732.
Donnelly, T. G., 1973, Algorithm 462, Bivariate Normal Distribution: Communications of the ACM, v. 16, p. 638.
Duckstein, L., and Kisiel, C. C., 1971, Efficiency of Hydrologic Data Collection Systems: Role of Type I and Type II Errors: Water Resour. Res. v. 7, p. 592–604.
Gershon, M., 1983, Optimal Drillhole Location Using Geostatistics: Society of Mining Engineers preprint 83–63.
Guertin, K., 1987, A Correction Model for Conditional Bias in Selective Mining Operations: Math. Geol., v. 19, p. 407–423.
Journel, A. G., and Huijbregts, C., 1978, Mining Geostatistics: Academic Press, London, 600 p.
Knudsen, H. P., and Fritz, C. B., 1989, Using IK to Determine Pod Boundaries in a Karst Lignite Deposit: Proceedings of the 21st APCOM Symposium, Society of Mining Engineers, New York, p. 227–236.
Marcotte, D., and David, M., 1985, The Bi-Gaussian Approach: A Simple Method for Recovery Estimation: Math. Geol., v. 17, p. 625–644.
Mardia, K. V., Kent, J. T., and Bibby, J. M., 1979, Multivariate Analysis: Academic Press, London, 521 p.
Moss, M. E., 1979, Some Basic Considerations in the Design of Hydrologic Data Networks: Water Resour. Res., v. 15, p. 1673–1676.
Rendu, J.-M., 1978, An Introduction to Geostatistical Methods of Mineral Evaluation: South African Institute of Mining and Metallurgy, Johannesburg, 84 p.
Rodriguez-Iturbe, I., and Mejia, J. M., 1974, The Design of Rainfall Networks in Time and Space: Water Resour. Res., v. 12, p. 1185–1195.
Solow, A. R., 1986, Mapping by Simple Indicator Kriging: Math. Geol., v. 18, p. 335–352.
Veneziano, D., and Kitanidis, P. K., 1982, Sequential Sampling to Contour an Uncertain Function: Math. Geol., v. 14, p. 387–404.
Verly, G., 1983, The Multigaussian Approach and its Applications to the Estimation of Local Reserves: Math. Geol., v. 15, p. 263–290.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Aspie, D., Barnes, R.J. Infill-sampling design and the Cost of classification errors. Math Geol 22, 915–932 (1990). https://doi.org/10.1007/BF00890117
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF00890117