In this paper, we address the extraction of rankings from multi-indicator systems, as a problem of approximation between the so-called “mutual ranking probability” matrices, associated to the partial order relations derived from the data. After providing a theoretical treatment of the topic, we propose a practical algorithm for ranking extraction and show it in action on a real example, pertaining to regional competitiveness
Using mutual ranking probabilities for dimensionality reduction and ranking extraction in multidimensional systems of ordinal variables / Fattore, M; Arcagni, A. - (2018), pp. 117-124. (Intervento presentato al convegno International Conference on Advances in Statistical Modelling of Ordinal Data tenutosi a Naples).
Using mutual ranking probabilities for dimensionality reduction and ranking extraction in multidimensional systems of ordinal variables
Arcagni, A
2018
Abstract
In this paper, we address the extraction of rankings from multi-indicator systems, as a problem of approximation between the so-called “mutual ranking probability” matrices, associated to the partial order relations derived from the data. After providing a theoretical treatment of the topic, we propose a practical algorithm for ranking extraction and show it in action on a real example, pertaining to regional competitiveness| File | Dimensione | Formato | |
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