Multi-Indicator Systems and Modelling in Partial Order

Part A: Theory.- Evaluation as a general approach to problem driven mathematical modeling.- Multivariate Data Sets for Inference of Order: Some Considerations and Explorations.- Measures of Incomparability and of Inequality and their Applications.- Measuring structural dissimilarity between finite partial orders.- Measuring complexity of partially ordered sets.- Part B: Partial Order as Tool to Analyse Composite Indicators.- Comparative Knowledge Discovery with Partial Order and Composite Indicator.- A software platform Towards a Comparison of Cars - A case study for Handling Ratio-Based Decisions.- Part C: New Trends in Partial Order.- Coordination of Contrariety and Ambiguity in Comparative Compositional Contexts: Balance of Normalized Definitive Status in Multi-indicator Systems.- Partial orders in socio-economics: an applicative challenge for poset theorists or a cultural challenge for social scientists.- Part D: Applications.- Ranking Hazardous Chemicals with a heuristic Approach to reduce Isolated Objects in Hasse Diagrams.- Hasse diagram Technique can further improve the interpretation of results in multi-elemental large-scale biomonitoring studies of atmospheric metal pollution.- Application of Partial Orders and Hasse Matrices in Ranking Contaminated sites.- Evaluating Ranking Robustness in Multi-indicator uncertain matrices: An application based on Simulation and Global Sensitivity Analysis.- Hasse Diagram technique Contributions to Environmental Risk Assessment.- Part E: Software Aspects.- PARSEC: an R package for poset-based evaluation in socioeconomic sciences.- Higher-Order indicator with Rank-Related Clustering in Multi-Indicator Systems.- Pyhasse Software Features Applied on the Evaluation of Chemicals in Human Breast Milk Samples in Turkey.- Indicator Analyses, What is important - and for what?.- PyHasse software for partial order analysis; Scientific background and description of some modules.- Index.