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.
"Multi-indicator Systems and Modelling in Partial Order" contains the newest theoretical concepts as well as new applications or even applications, where standard multivariate statistics fail. Some of the presentations have their counterpart in the book; however, there are many contributions, which are completely new in the field of applied partial order.
Includes techniques to derive weak orders out of the data matrix with as few restrictions as possible
Analyzes incomparabilities as a topic of its own right, and as an aspect of increasing importance
Informs about recent developments in theory and in applications in the field of partial order