PCA reduces dozens of variables (e.g., particle size bins, mineral abundance, XRD peaks) into a few uncorrelated “principal components.”
When formulating a collector blend (e.g., xanthate + dithiophosphate + mercaptan), the proportions sum to 100%. Standard factorial designs fail here. Mixture designs (simplex lattice, extreme vertices) are required. They model synergistic and antagonistic effects correctly.
The students watched as statistics moved from abstraction to consequence. One night, a younger engineer named Mateo asked, “Which method is right? Kriging, simulation, indicator—how do we pick?”
Quantifying uncertainties that arise from measurement errors and the heterogeneous nature of ore.
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Statistical — Methods For Mineral Engineers
PCA reduces dozens of variables (e.g., particle size bins, mineral abundance, XRD peaks) into a few uncorrelated “principal components.”
When formulating a collector blend (e.g., xanthate + dithiophosphate + mercaptan), the proportions sum to 100%. Standard factorial designs fail here. Mixture designs (simplex lattice, extreme vertices) are required. They model synergistic and antagonistic effects correctly. Statistical Methods For Mineral Engineers
The students watched as statistics moved from abstraction to consequence. One night, a younger engineer named Mateo asked, “Which method is right? Kriging, simulation, indicator—how do we pick?” PCA reduces dozens of variables (e
Quantifying uncertainties that arise from measurement errors and the heterogeneous nature of ore. PCA reduces dozens of variables (e.g.
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