Discussion - On nonnegative weights of linear kriging estimation

G.M. Philip and D.F. Watson The article cited above reflects the difficulty that is often encountered in interpreting different aspects of kriging. Baafi et al. write : "Due to negative kriging weights, negative block grades may be obtained in some extreme situations, which makes no practical sense." Their solution to this particular problem is to constrain the kriged estimates to data values that have positive weights, i.e., reduce the subset size contributing to the estimation. As Journel (1986, p. 133) has already observed, "Negative weights are no evil." Indeed, they are an ineluctable result of the Lagrangian multipliers in the system of simultaneous equations. The fact that data distant from the estimation point may be given negative weights simply means that the influence of such distant values must be negated because their influence is contradictory to closer values (as illustrated by Baafi et al. in their Figs. 3 and 4). Of course negative kriging weights applied to distant grade values will not in themselves induce negative grade at some central interpolation point. Negative grade values, rather, seem to be a particular artifact of automatic methods of estimation involving accu¬mulations (Philip and Watson, 1985a, 1985b, 1987b). The elimination of negative weights, suggested by Baafi et al., is likely to exacerbate a quite different problem of kriging and piecewise spline interpolation discussed elsewhere (Philip and Watson, 1987a). In interpolating large data sets of scattered observations, changing local subsets or neighborhoods must be selected automatically. Because of the mathematical formulation of kriging and spline interpolation, discontinuities then occur between closely-spaced estimation points as the subset used in the estimation changes. If this subset is reduced in number and size, the discontinuities will be amplified and more common. ? References Journel, A.G., 1986, "Geostatistics: models and tools for Earth Sciences," Journal of Mathematical Geology, Vol. 18, No. 1, pp. 119-139. Philip, G.M., and Watson, D.F., 1985a, "Theoretical aspects of grade-tonnage calculations," International Journal of Mining and Geological Engineering, Vol. 3, pp. 149-154. Philip, G.M., and Watson, D.F., 1985b, "A deterministic approach to computing ore reserves. I, Grade Estimation," Earth Resources Foundation, Occas. Paper 2, The University of Sydney, 24 pp. Philip, G.M., and Watson, D.F., 1987a, "Neighborhood discontinuities in bivariate interpolation of scattered observations," Mathematical Geology, Vol. 18, No. 1, pp. 69-74. Philip, G.M., and Watson, D.F., 1987b, "Estimating interactions of topological functions," Mathematical Geology, Vol. 18, (at press). Reply by Y. C. Kim Before replying to the comments by Philip and Watson, it is desirable to establish the original perspective of our paper, which was intended primarily for the practitioners of mining who possess a working knowledge of ordinary kriging. The paper tried to convey the following practical points: (1) there are circumstances in which one observes negative weights, (2) illustration of circumstances under which one can expect negative weights, (3) should one obtain a negative estimated grade, one can resort to elimination of negative weights using the technique outlined in the paper, and (4) one could normally select only the first layer of surrounding assays to estimate the block grade. Under such a perspective, most of the comments by Philip and Watson are irrelevant and misdirected. For example, the practitioners do not find it difficult to "interpret" the results of ordinary kriging, as evidenced by the fact that they have been using the results for nearly a decade. Nor are the practitioners concerned with discontinuities in estimated block grades due to changing neighborhood of assays during kriging. What matters to the practitioners is the fact that kriging does provide the best estimate among all the estimation tools available to them as of today. ?