Interpreting exploration geochemical data from Outokumpu, Finland: a MVE-robust factor analysis

Abstract

Abstract A factor analysis (FA) rendered robust using the minimum volume ellipsoid (MVE) estimator was carried out on geochemical till data consisting of 622 observations on 21 variables (Al, Ba, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Ni, P, Sc, Sr, Th, Ti, V, Y, Zn) from Outokumpu, Finland. The distribution of the majority of variables is slightly to moderately positively skewed. A robust, three-factor model accounting for 82.1% of the total variance was fitted. The fitted model delineates zones related to geology, ore deposits, mineralized horizons, and background variation. The robust FA generally outperforms an otherwise identical classical FA with clearer definition of lithology, background variation, and, in particular, greatly sharpens the anomaly contrasts over mineralization. Both classical and robust factor scores successfully define regional patterns with respect to geology, mineralization and surficial environments. However, both the number and magnitude of scores exceeding 2.0 has increased, from classical FA to robust FA, for all three factors. Such enhancements facilitate the identification of geochemical anomalies, particularly subtle anomalies of the kind commonly associated with till data. This study indicates that the presence of outlying data points can exert a strong masking effect on the identification of geochemical anomalies in classical FA.