Synthetic indicators are widely used to summarize multi-dimensional phenom- ena into a single value, using different aggregation methods. This paper proposes a novel approach based on Functional Data Analysis to evaluate the impact of different aggregation methods and weighting schemes. The proposal is based on analysing the distances between different synthetic indicators and their dimensions, considering their temporal evolution.
Salvatore Alaimo, L., Fortuna, F., Naccarato, A. (2025). Evaluation of Synthetic Indicators: a new method based on functional data analysis. In B.E. Boccuzzo G. (a cura di), Book of short papers 2025 Conference of the 12th Scientific Meeting of the Statistics for the Evaluation and Quality of Services Group of the Italian Statistical Society (SVQS) IES 2025 (pp. 739-745). Padova : Coop. Libraria Editrice Università di Padova.
Evaluation of Synthetic Indicators: a new method based on functional data analysis
Francesca Fortuna;Alessia Naccarato
2025-01-01
Abstract
Synthetic indicators are widely used to summarize multi-dimensional phenom- ena into a single value, using different aggregation methods. This paper proposes a novel approach based on Functional Data Analysis to evaluate the impact of different aggregation methods and weighting schemes. The proposal is based on analysing the distances between different synthetic indicators and their dimensions, considering their temporal evolution.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
