A correction model for conditional bias in selective mining operations |
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| Authors: | Kateri Guertin |
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| Institution: | (1) Institut National de la Recherche Scientifique, Universite du Quebec, 2700 Einstein St., G1V 4C7 Sainte-Foy, Quebec, Canada |
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| Abstract: | A nonlinear correction functionK(Z*) is proposed to transform any initial linear grade estimatorZ* into a conditional unbiased estimatorZ**=K(Z*) with reduced conditional estimation variance. Such a corrected estimator allows more accurate prediction of ore reserves at any level of selection performed during the mine lifetime. The correction is based upon an analytical or isofactorial representation of a bivariate distribution model of true gradeZ and its estimatorZ*. This correction model allows derivation of conditional estimation variances for both estimatorsZ* andZ** and provides a solution to the problem of change of support. A case study is presented and performance of the proposed correction model is evaluated in terms of actual conditional bias and mean squared errors. Results obtained stress the practical importance of the correction model in selective mining operations. |
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| Keywords: | Conditionally unbiased estimator correction function selective mining operations |
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