The application of ILR transromed data factor analysis to delineating geochemical anomalies
Guo-Shuai GENG1,2, Fan YANG3,4(), Jian-Na GUO5
1. School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China 2. Gold Geological Institute of CAPF, Langfang 065000, China 3. Beijing Institute of Geology for Mineral Resources, Beijing 100012, China 4. Research Center of Geochemical Survey and Assessment on Land Quality, China Geological Survey, Langfang 065000, China 5. Natural Resources and Planning Bureau, Langfang 065000, China
The reliable detection of data outliers and unusual data behavior is one of the key task in the statistical analysis of applied geochemical data, and has remained a core problem. Factor analysis is a multivariate statistical analysis method, which is used to solve the problem of complex geological origin and superimposed mineralization; nevertheless, geochemical data are compositional data, there exist their closure effects, closure has a major influence on the covariance and correlation matrices, the very base of principal component analysis (PCA) and factor analysis (FA). So the authors applied isometric logratio-transformed (ILR) to 'open' the data before FA. The study area is located in the east of East Kunlun polymetallic mineralization zone. The authors used ILR transformed 11 major elements to conduct FA, extracted four public factors and calculated the four factor scores. According to the results of FA with EDA method , the authors standardized geochemical data and delineated Au anomaly. Compared with traditional method, this method can eliminate the influence of high background values.
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