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.