Identification of multivariate geochemical anomalies using spatial autocorrelation analysis and robust statistics

Multivariate geochemical anomaly identification is one of the most important tasks in exploration geochemical data analysis. This paper proposes a new approach to identify multivariate geochemical anomalies which accounts for the degree of spatial autocorrelation among observations. This method is a combination of Robust Mahalanobis Distance (RMD), spatial autocorrelation analysis and robust statistics. The Minimum Covariance Determinant (MCD)...