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M. Fattore and A. Arcagni
and systems, like the healthcare, the educational or the welfare systems), where the
“posetic perspective” may well be a key factor to support governance and decisionmaking.
References
Annoni, P., & Bruggemann, R. (2009). Exploring partial order of European countries. Social
Indicators Research, 92(3), 471.
Arcagni, A. (2017). PARSEC: An R package for partial orders in socio-economics. In M. Fattore
& R. Bruggemann (Eds.), Partial order concepts in applied sciences (pp. 275–289). Cham:
Springer.
Arcagni, A., di Belgiojoso, E. B., 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, 551–579.
Bachtrögler, J., Badinger, H., de Clairfontaine, A. F., & Reuter, W. H. (2016). Summarizing
data using partially ordered set theory: An application to fiscal frameworks in 97 countries.
Statistical Journal of the IAOS, 32(3), 383–402.
Badinger, H., & Reuter, W. H. (2015). Measurement of fiscal rules: Introducing the application of
partially ordered set (poset) theory. Journal of Macroeconomics, 43, 108–123.
Bruggemann, R., & Patil, G. P. (2011). Ranking and prioritization for multi-indicator systems:
Introduction to partial order applications. New York: Springer Science & Business Media.
Caperna, G., & Boccuzzo, G. (2018). Use of poset theory with big datasets: A new proposal applied
to the analysis of life satisfaction in italy. Social Indicators Research, 136(3), 1071–1088.
Carlsen, L. (2017). An alternative view on distribution keys for the possible relocation of refugees
in the european union. Social Indicators Research, 130(3), 1147–1163.
Carlsen, L., & Bruggemann, R. (2014). The ‘failed state index’ offers more than just a simple
ranking. Social Indicators Research, 115(1), 525–530.
Carlsen, L., & Bruggemann, R. (2017). Fragile state index: Trends and developments. A partial
order data analysis. Social Indicators Research, 133(1), 1–14.
Davey, B. A., & Priestley, H. A. (2002). Introduction to lattices and order. Cambridge: Cambridge
University Press.
De Loof, K. (2009). Efficient computation of rank probabilities in posets. Ph.D. thesis, Ghent
University.
De Loof, K., De Meyer, H., & De Baets, B. (2006). Exploiting the lattice of ideals representation
of a poset. Fundamenta Informaticae, 71(2–3), 309–321.
De Loof, K., De Baets, B., & De Meyer, H. (2008). Properties of mutual rank probabilities
in partially ordered sets. In Multicriteria ordering and ranking: Partial orders, ambiguities
and applied issues (pp. 145–165). Warsaw: Systems Research Institute, Polish Academy of
Sciences.
di Bella, E., Gandullia, L., Leporatti, L., Montefiori, M., & Orcamo, P. (2018). Ranking and
prioritization of emergency departments based on multi-indicator systems. Social Indicators
Research, 136(3), 1089–1107.
Fattore, M. (2016). Partially ordered sets and the measurement of multidimensional ordinal
deprivation. Social Indicators Research, 128(2), 835–858.
Fattore, M. (2017). Functionals and synthetic indicators over finite posets. In M. Fattore & R.
Bruggemann (Eds.), Partial order concepts in applied sciences (pp. 71–86). Cham: Springer.
Fattore, M., & Arcagni, A. (2018). F-FOD: Fuzzy first order dominance analysis and populations
ranking over ordinal multi-indicator systems. Social Indicators Research, 1–29. First online.
M. Fattore and A. Arcagni
and systems, like the healthcare, the educational or the welfare systems), where the
“posetic perspective” may well be a key factor to support governance and decisionmaking.
References
Annoni, P., & Bruggemann, R. (2009). Exploring partial order of European countries. Social
Indicators Research, 92(3), 471.
Arcagni, A. (2017). PARSEC: An R package for partial orders in socio-economics. In M. Fattore
& R. Bruggemann (Eds.), Partial order concepts in applied sciences (pp. 275–289). Cham:
Springer.
Arcagni, A., di Belgiojoso, E. B., 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, 551–579.
Bachtrögler, J., Badinger, H., de Clairfontaine, A. F., & Reuter, W. H. (2016). Summarizing
data using partially ordered set theory: An application to fiscal frameworks in 97 countries.
Statistical Journal of the IAOS, 32(3), 383–402.
Badinger, H., & Reuter, W. H. (2015). Measurement of fiscal rules: Introducing the application of
partially ordered set (poset) theory. Journal of Macroeconomics, 43, 108–123.
Bruggemann, R., & Patil, G. P. (2011). Ranking and prioritization for multi-indicator systems:
Introduction to partial order applications. New York: Springer Science & Business Media.
Caperna, G., & Boccuzzo, G. (2018). Use of poset theory with big datasets: A new proposal applied
to the analysis of life satisfaction in italy. Social Indicators Research, 136(3), 1071–1088.
Carlsen, L. (2017). An alternative view on distribution keys for the possible relocation of refugees
in the european union. Social Indicators Research, 130(3), 1147–1163.
Carlsen, L., & Bruggemann, R. (2014). The ‘failed state index’ offers more than just a simple
ranking. Social Indicators Research, 115(1), 525–530.
Carlsen, L., & Bruggemann, R. (2017). Fragile state index: Trends and developments. A partial
order data analysis. Social Indicators Research, 133(1), 1–14.
Davey, B. A., & Priestley, H. A. (2002). Introduction to lattices and order. Cambridge: Cambridge
University Press.
De Loof, K. (2009). Efficient computation of rank probabilities in posets. Ph.D. thesis, Ghent
University.
De Loof, K., De Meyer, H., & De Baets, B. (2006). Exploiting the lattice of ideals representation
of a poset. Fundamenta Informaticae, 71(2–3), 309–321.
De Loof, K., De Baets, B., & De Meyer, H. (2008). Properties of mutual rank probabilities
in partially ordered sets. In Multicriteria ordering and ranking: Partial orders, ambiguities
and applied issues (pp. 145–165). Warsaw: Systems Research Institute, Polish Academy of
Sciences.
di Bella, E., Gandullia, L., Leporatti, L., Montefiori, M., & Orcamo, P. (2018). Ranking and
prioritization of emergency departments based on multi-indicator systems. Social Indicators
Research, 136(3), 1089–1107.
Fattore, M. (2016). Partially ordered sets and the measurement of multidimensional ordinal
deprivation. Social Indicators Research, 128(2), 835–858.
Fattore, M. (2017). Functionals and synthetic indicators over finite posets. In M. Fattore & R.
Bruggemann (Eds.), Partial order concepts in applied sciences (pp. 71–86). Cham: Springer.
Fattore, M., & Arcagni, A. (2018). F-FOD: Fuzzy first order dominance analysis and populations
ranking over ordinal multi-indicator systems. Social Indicators Research, 1–29. First online.