title: Exploratory analysis of data sets with missing elements and outliers.
abstract: The main goal of the presented paper was to develop a general strategy allowing exploration of contaminated data sets with missing elements, based on application of robust PLS for initial estimation of missing elements. Using robust distance, the outlying elements were identified. After their identification and replacing by missing elements, the expectation-maximization algorithm (which can be built in into different computational procedures, such as principal component analysis and its generalisation to the N-way data-the TUCKER3 model) was used for construction of the final model.
mesh_terms: D015258:Acid Rain / Q000032:analysis; D000397:Air Pollution / Q000032:analysis; D001317:Austria; D004784:Environmental Monitoring / Q000379:methods*; D007477:Ions / Q000032:analysis; D008962:Models, Theoretical; D015999:Multivariate Analysis
chemical_list: D015258:Acid Rain; D007477:Ions