Quadratic investigation of geochemical distribution by backward elimination approach at Glojeh epithermal Au(Ag)-polymetallic mineralization, NW Iran

Abstract

The correspondence analysis will describe elemental association accompanying an indicator samples. This analysis indicates strong mineralization of Ag, As, Pb, Te, Mo, Au, Zn and to a lesser extent S, W, Cu at Glojeh polymetallic mineralization, NW Iran. This work proposes a backward elimination approach (BEA) that quantitatively predicts the Au concentration from main effects (X), quadratic terms (X²) and the first order interaction (X_i×X_j) of Ag, Cu, Pb, and Zn by initialization, order reduction and validation of model. BEA is done based on the quadratic model (QM), and it was eliminated to reduced quadratic model (RQM) by removing insignificant predictors. During the QM optimization process, overall convergence trend of R², R²(adj) and R²(pred) is obvious, corresponding to increase in the R²(pred) and decrease of R². The RQM consisted of (threshold value, Cu, Ag×Cu, Pb×Zn, and Ag²–Pb²) and (Pb, Ag×Cu, Ag×Pb, Cu×Zn, Pb×Zn, and Ag²) as main predictors of optimized model according to 288 and 679 litho-samples in trenches and boreholes, respectively. Due to the strong genetic effects with Au mineralization, Pb, Ag², and Ag×Pb are important predictors in boreholes RQM, while the threshold value is known as an important predictor in the trenches model. The RQMs R²(pred) equal 74.90% and 60.62% which are verified by R² equal to 73.9% and 60.9% in the trenches and boreholes validation group, respectively.

Keywords

correspondence analysis / first order interaction / reduced quadratic model (RQM) / optimized model / order reduction and validation / strong genetic effects

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