MONTOYA, C; EMERY, X.; RUBIO, E. and WIERTZ, J.. Multivariate resource modelling for assessing uncertainty in mine design and mine planning. J. S. Afr. Inst. Min. Metall. [online]. 2012, vol.112, n.5, pp. 353363. ISSN 24119717.


2. DEUTSCH, C.V., and JOURNEL, A.G. GSLIB: Geostatistical Software Library and User's Guide, 2nd edn. New York, Oxford University Press, 1998. pp. 369. [ Links ] 3. JOURNEL, A.G., and HUIJBREGTS, C.J. Mining Geostatistics. London, Academic Press, 1978. pp. 600. [ Links ] 4. JOURNEL, A.G. Geostatistics for conditional simulation of orebodies. Economic Geology, vol. 69, no. 5, 1974. pp. 673687. [ Links ] 5. JOURNEL, A.G., and KYRIAKIDIS, P.C. Evaluation of mineral reserves: a simulation approach. Oxford, Oxford University Press, 2004. pp. 216. [ Links ] 6. DOHM, C.E. Applications of simulation techniques for combined risk assessment of both geological and grade models  an example. 31st International Symposium on Computer Applications in the Minerals Industry APCOM, Cape Town, Johannesburg, 1416 May 2003. The South African Institute of Mining and Metallurgy, 2003. pp. 351354. [ Links ] 7. SNOWDEN, D.V. Practical Interpretation of Mineral Resources and Ore Reserve Classification Guidelines. Mineral Resource and Ore Reserve Estimation  the AusIMM Guide to Good Practice. Edwards, A.C. (ed.). Melbourne. The Australasian Institute of Mining and Metallurgy, 2001. pp. 643653. [ Links ] 8. WACKERNAGEL, H. Multivariate Geostatistics: An Introduction with Applications, 3rd edn. Berlin, Springer, 2003. pp. 387. [ Links ] 9. GOULARD, M. and VOLTZ, M. Linear coregionalization model: tools for estimation and choice of crossvariogram matrix. Mathematical Geology, vol. 24, no. 3, 1992. pp. 269286. [ Links ] 10. EMERY, X. Iterative algorithms for fitting a linear model of coregionalization. Computers & Geosciences, vol. 36, no. 9, 2010. pp. 11501160. [ Links ] 11. EMERY, X. and LantuSjoul, C. TBSIM: a computer program for conditional simulation of threedimensional Gaussian random fields via the turning bands method. Computers & Geosciences, vol. 32, no. 10, 2006. pp. 16151628. [ Links ] 12. EMERY, X. A turning bands program for conditional cosimulation of crosscorrelated Gaussian random fields. Computers & Geosciences, vol. 34, no. 12, 2008. pp. 18501862. [ Links ] 13. LEUANGTHONG, O., MCLENNAN, J.A., and DEUTSCH, C.V. Minimum acceptance criteria for geostatistical realizations. Natural Resources Research, vol. 13, no. 3, 2004. pp. 131141. [ Links ] 14. DUBRULE, O. Estimating or choosing a geostatistical model? Geostatistics for the Next Century. Dimitrakopoulos, R. (ed.). Dordrecht. Kluwer Academic, 1994. pp. 314. [ Links ] 15. PARDOIGUZQUIZA, E. Bayesian inference of spatial covariance parameters. Mathematical Geology, vol. 31, no. 1, 1999. pp. 4765. [ Links ] 16. DOWD, P.A. and PARDOIGUZQUIZA, E. The incorporation of model uncertainty in geostatistical simulation. Geographical and Environmental Modelling, vol. 6, no. 2, 2002. pp. 147169. [ Links ] 17. EMERY, X. Statistical tests for validating geostatistical simulation algorithms. Computers & Geosciences, vol. 34, no. 11, 2008. pp. 16101620. [ Links ] 18. LANTUEJOUL, C. Ergodicity and integral range. Journal of Microscopy, vol. 161, no. 3, 1991. pp. 387403. [ Links ] 19. KRIGE, D.G. A practical analysis of the effects of spatial structure and of data available and accessed, on conditional biases in ordinary kriging. Geostatistics Wollongong '96. Baafi, E.Y., and Schofield, N.A. (eds.). Dordrecht, Kluwer Academic, 1997. pp. 799810. [ Links ] 20. MATHERON, G. The selectivity of the distributions and the second principle of geostatistics. Geostatistics for Natural Resources Characterization. Verly, G., David, M., Journel, A.G., and Marechal, A. (eds.). Dordrecht, Reidel, 1984. pp. 421433. [ Links ] 21. VANN, J., JACKSON, S., and BERTOLI, O. Quantitative kriging neighbourhood analysis for the mining geologist  a description of the method with worked case examples. 5th International Mining Geology Conference, Melbourne. The Australasian Institute of Mining and Metallurgy, 2003. pp. 215223. [ Links ] 22. LERCHS, H. and GROSSMANN, I.F. Optimum design of openpit mines. CIM Bulletin, vol. 58, 1965. pp. 1724. [ Links ] 23. WHITTLE, J. Open Pit Optimization, Surface Mining, 2nd edn. AME, 1990. pp. 470475. [ Links ] 24. ISAAKS, E. The kriging oxymoron: a conditionally unbiased and accurate predictor. (2nd edn). Geostatistics Banff2004. Leuangthong, O., and Deutsch, C.V. (eds.). Dordrecht. Springer, 2005. pp. 363374. [ Links ] 25. DIMITRAKOPOULOS, R., FARRELLY, C.T., and GODOY, M.Moving forward from traditional optimization: grade uncertainty and risk effects in openpit design. Transactions of the Institute of Materials, Minerals and Mining. Section A: Mining Technology, vol. 111, no. 1, 2002. pp. 8288. [ Links ] 26. NICHOLAS, G.D., COWARD, S.J, and FERREIRA, J. Financial risk assessment using conditional simulation in an integrated evaluation model. Eighth International Geostatistics Congress Geostats2008. Ortiz, J.M. and Emery, X. (eds.). Santiago. Gecamin Ltda, 2008. Pp.759768. [ Links ] 27. RIVOIRARD, J. On some simplifications of cokriging neighborhood. Mathematical Geology, vol. 36, no. 8, 2004. pp. 899915. [ Links ] 28. SUBRAMANYAM, A. and PANDALAI, H.S. On the equivalence of the cokriging and kriging systems. Mathematical Geology, vol. 36, no. 4, 2004. pp. 507523. [ Links ] 29. SUBRAMANYAM, A. and PANDALAI, H.S. Data configurations and the cokriging system: simplification by screen effects. Mathematical Geosciences, vol. 40, no. 4, 2008. pp. 425443. [ Links ] 