Research
Publications
Alaimo, L. S., Arcagni, A., Di Bella, E., Maggino, F., & Trapani, M. (2019). AIQUAV 2019: VI convegno nazionale dell’associazione italiana per gli studi sulla qualità della vita: Benessere collettivo e scelte individuali: Fiesole (FI), 12-14 dicembre 2019: Libro dei contenuti brevi. AIQUAV 2019, 1–284. https://gup.unige.it/node/300
Alaimo, L. S., Arcagni, A., Fattore, M., & Maggino, F. (2020). Synthesis of multi-indicator system over time: A poset-based approach. Social Indicators Research, 1–23.
Alaimo, L. S., Arcagni, A., Fattore, M., Maggino, F., & Quondamstefano, V. (2020). Measuring equitable and sustainable well-being in italian regions: The non-aggregative approach. https://doi.org/10.1007/s11205-020-02388-7
Arcagni, A. (2014a). Income distribution at flint: A comparison of the inequality with other american cities. Flint One City 100 Years Under Variability.
Arcagni, A. (2014b). Zenga distribution: Parameters estimation with contraints on synthetic inequality indices.
Arcagni, A. (2017a). On the decomposition by sources of the zenga 1984 point and synthetic inequality indexes. Statistical Methods & Applications, 26(1), 113–133.
Arcagni, A. (2017b). PARSEC: An r package for partial orders in socio-economics. In Partial order concepts in applied sciences (pp. 275–289). Springer.
Arcagni, A., Avellone, A., & Fattore, M. (2022). Complexity reduction and approximation of multidomain systems of partially ordered data. Computational Statistics & Data Analysis, 107520.
Arcagni, A., & Bagnato, L. (2009). Smooth backfitting with r.
Arcagni, A., Belgiojoso, E. B. di, Fattore, M., & Rimoldi, S. M. L. (2017). Un nuovo approccio per la valutazione della povertà tra gli stranieri attraverso variabili ordinali. Giornate Di Studio Sulla Popolazione 2017.
Arcagni, A., Belgiojoso, E. B. di, Fattore, M., & Rimoldi, S. M. L. (2018). Analyzing deprivation and fragility patterns of migrants in lombardy, using partially ordered sets and self-organizing maps. European Population Conference 2018.
Arcagni, A., Belgiojoso, E. B. di, Fattore, M., & Rimoldi, S. M. L. (2019). Multidimensional analysis of deprivation and fragility patterns of migrants in lombardy, using partially ordered sets and self-organizing maps. Social Indicators Research, 141(2), 551–579.
Arcagni, A., Candila, V., & Grassi, R. (2022). A new model for predicting the winner in tennis based on the eigenvector centrality. Annals of Operations Research, 1–18.
Arcagni, A., Cerqueti, R., & Grassi, R. (2024). Higher-order assortativity for directed weighted networks and markov chains. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2024.02.031
Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2017). Higher order assortativity in complex networks. European Journal of Operational Research, 262(2), 708–719. https://doi.org/10.1016/j.ejor.2017.04.028
Arcagni, A., Grassi, R., Stefani, S., & Torriero, A. (2019). Extending assortativity: An application to weighted social networks. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2019.10.008
Arcagni, A., & Porro, F. (2013). On the parameters of zenga distribution. Statistical Methods & Applications, 22(3), 285–303.
Arcagni, A., & Porro, F. (2014). The graphical representation of inequality. Revista Colombiana de Estadistica, 37(2), 419–437. https://doi.org/10.15446/rce.v37n2spe.47947
Arcagni, A., & Porro, F. (2016). A comparison of income distributions models through inequality curves. Statistica & Applicazioni, 14(2).
Arcagni, A., & Zenga, M. (2013). Application of zenga’s distribution to a panel survey on household incomes of european member states. Statistica & Applicazioni, 11(1).
Arcagni, A., & Zenga, M. (2014). Decomposition by sources of the \(\xi\) inequality index. Scientific Meeting of the Italian Statistical Society-11/13 June.
Fattore, M., & Arcagni, A. (2013). Measuring multidimensional polarization with ordinal data. SIS 2013 Statistical Conference, BES-M3.
Fattore, M., & Arcagni, A. (2014). PARSEC: An r package for poset-based evaluation of multidimensional poverty. In Multi-indicator systems and modelling in partial order (pp. 317–330). Springer. https://doi.org/10.1007/s10479-022-04594-7
Fattore, M., & Arcagni, A. (2018a). A reduced posetic approach to the measurement of multidimensional ordinal deprivation. Social Indicators Research, 136(3), 1053–1070.
Fattore, M., & Arcagni, A. (2018b). Using mutual ranking probabilities for dimensionality reduction and ranking extraction in multidimensional systems of ordinal variables.
Fattore, M., & Arcagni, A. (2019). F-FOD: Fuzzy first order dominance analysis and populations ranking over ordinal multi-indicator systems. Social Indicators Research, 144(1), 1–29.
Fattore, M., Arcagni, A., & Barberis, S. (2014). Visualizing partially ordered sets for socioeconomic analysis. Revista Colombiana de Estadı́stica, 37(2), 437–450. https://doi.org/10.15446/rce.v37n2spe.47948
Fattore, M., Arcagni, A., & Maggino, F. (2019). Optimal scoring of partially ordered data, with an application to the ranking of smart cities.
Fattore, M., Busetta, A., Mendola, D., & Arcagni, A. (2014). A fuzzy approach to multidimensional material deprivation measurement: The case of foreigners living in italy. EPC 2014 Budapest, Hungary, 25-28 June 2014.
Fattore, M., Grassi, R., & Arcagni, A. (2014). Measuring structural dissimilarity between finite partial orders. In Multi-indicator systems and modelling in partial order (pp. 69–84). Springer.
Fattore, M., Maggino, F., & Arcagni, A. (2015). Exploiting ordinal data for subjective well-being evaluation. Statistics in Transition New Series, 3(16), 409–428. https://doi.org/10.21307/stattrans-2015-023
Fattore, M., Maggino, F., & Arcagni, A. (2016). Non-aggregative assessment of subjective well-being. In Topics in theoretical and applied statistics (pp. 227–237). Springer. https://doi.org/10.1007/978-3-319-27274-0_20
Grassi, R., Fattore, M., & Arcagni, A. (2015). Structural and non-structural temporal evolution of socio-economic real networks. Quality & Quantity, 49(4), 1597–1608.
Simin, P. T., Jafari, G. R., Ausloos, M., Caiafa, C. F., Caram, F., Sonubi, A., Arcagni, A., & Stefani, S. (2018). Dynamical phase diagrams of a love capacity constrained prey–predator model. The European Physical Journal B, 91(2), 1–18. https://doi.org/10.1140/epjb/e2017-80531-7
Sonubi, A., Arcagni, A., Stefani, S., & Ausloos, M. (2016). Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity. Physical Review E, 94(2), 022303. https://doi.org/10.1103/physreve.94.022303
Zenga, M., & Arcagni, A. (2011). Estimating the three parameters of zenga’s distribution for income by size. Int. Statistical Inst.: Proc. 58th World Statistical Congress, 2011, Dublin (Session CPS016).
Zenga, M., & Arcagni, A. (2012). Application of zenga’s distribution to a panel survey on household incomes of european member states.
Zenga, M., Porro, F., & Arcagni, A. (2010). Method of moments for zenga’s distribution.
PhD Thesis
Arcagni, Alberto (2011). La determinazione dei parametri di un nuovo modello distributivo per variabili non negative: aspetti metodologici e applicazioni. Università di Milano-Bicocca.