TY - JOUR ID - 57308 TI - Accuracy evaluation of different statistical and geostatistical censored data imputation approaches (Case study: Sari Gunay gold deposit) JO - International Journal of Mining and Geo-Engineering JA - IJMGE LA - en SN - 2345-6930 AU - Ghane, Babak AU - Asghari, Omid AD - Simulation and Data Processing Laboratory, University College of Engineering, School of Mining Engineering, University of Tehran, Tehran, Iran Y1 - 2016 PY - 2016 VL - 50 IS - 1 SP - 49 EP - 60 KW - Censored data KW - collocated cosimulation Markov model 2 KW - half detection KW - imputation KW - Multidimensional Scaling KW - multiple imputation DO - 10.22059/ijmge.2016.57308 N2 - Most of the geochemical datasets include missing data with different portions and this may cause a significant problem in geostatistical modeling or multivariate analysis of the data. Therefore, it is common to impute the missing data in most of geochemical studies. In this study, three approaches called half detection (HD), multiple imputation (MI), and the cosimulation based on Markov model 2 (MM2) are used to impute the censored data. According to the fact that the new datasets have to satisfy the original data underlying structure, the Multidimensional Scaling (MDS) approach has been used to explore the validity of different imputation methods. Log-ratio transformation (alr transformation) was performed to open the closed compositional data prior to applying the MDS method. Experiments showed that, based on the MDS approach, the MI and the MM2 could not satisfy the original underlying structure of the dataset as well as the HD approach. This is because these two mentioned approaches have produced values higher than the detection limit of the variables. UR - https://ijmge.ut.ac.ir/article_57308.html L1 - https://ijmge.ut.ac.ir/article_57308_544fbb4f9cbf3abc939d72797fee147a.pdf ER -