TY - JOUR ID - 53107 TI - The Use of Robust Factor Analysis of Compositional Geochemical Data for the Recognition of the Target Area in Khusf 1:100000 Sheet, South Khorasan, Iran JO - International Journal of Mining and Geo-Engineering JA - IJMGE LA - en SN - 2345-6930 AU - Keykha Hoseinpoor, Majid AU - Aryafar, Ahmad AD - Department of Mining, Faculty of Engineering, University of Birjand, Iran Y1 - 2014 PY - 2014 VL - 48 IS - 2 SP - 191 EP - 199 KW - compositional data KW - Iran KW - log-ratio transform KW - RCC KW - Stream Sediment DO - 10.22059/ijmge.2014.53107 N2 - The closed nature of geochemical data has been proven in many studies. Compositional data have special properties that mean that standard statistical methods cannot be used to analyse them. These data imply a particular geometry called Aitchison geometry in the simplex space. For analysis, the dataset must first be opened by the various transformations provided. One of the most popular of the applied transformations is the log-ratio transform. The main purpose of this research is to identify the anomalous area in the Khusf 1:100000 sheet which is located in the western part of Birjand, South Khorasan province. To achieve the goal, a dataset of 652 stream sediments geochemically analysed for 20 elements was collected. In practice, the geochemical data were first opened by CLR transformation and then the range correlation coefficient (RCC) ratio was calculated and mapped. In consequence, the robust factor analysis for compositional data was used to separate the elements, mostly in the high-value regions obtained by the method of RCC. Finally, the priority of anomalies was specified using weighted catchment analysis. The above procedures led to the recognition of some anomaly zones for elements of Cu, Bi, Sb, Ni and Cr in the study area. Such results can be useful for designing an appropriate exploratory plan for semi-detailed and detailed exploration steps. UR - https://ijmge.ut.ac.ir/article_53107.html L1 - https://ijmge.ut.ac.ir/article_53107_da80a840287281bce0fbf5069b57d0f8.pdf ER -