Uneingeschränkter Zugang

Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data

   | 26. Dez. 2019

Zitieren

Alonso, D.B., Androniceanu, A., Georgescu, I. (2016). Sensitivity and vulnerability of European countries in time of crisis based on a new approach to data clustering and curvilinear analysis. Administratie si Management Public, 27, 46.Search in Google Scholar

Aziz, S.A., Amin, R.M., Yusof, S.A., Haneef, M.A., Mohamed, M.O., Oziev, G. (2015). A critical analysis of development indices. Australian Journal of Sustainable Business and Society, 1 (01).Search in Google Scholar

Baker, B. (2011). World development: An essential text. New Internationalist.Search in Google Scholar

Bates, W. (2009). Gross national happiness. Asian-Pacific Economic Literature, 23 (2), 1–16.10.1111/j.1467-8411.2009.01235.xSearch in Google Scholar

Bock, H.H., Diday, E. (eds.) (2012). Analysis of symbolic data: exploratory methods for extracting statistical information from complex data. Springer Science & Business Media.Search in Google Scholar

Billard, L., Diday, E. (2006). Symbolic Data Analysis: Conceptual Statistics and Data Mining John Wiley.10.1002/9780470090183Search in Google Scholar

Brito, P. (2002). Hierarchical and pyramidal clustering for symbolic data. Journal of the Japanese Society of Computational Statistics, 15 (2), 231–244.10.5183/jjscs1988.15.2_231Search in Google Scholar

Brito, P. (1995). Symbolic objects: order structure and pyramidal clustering. Annals of Operations Research, 55 (2), 277–297.10.1007/BF02030863Search in Google Scholar

Dasgupta, S., Wheeler, D., Mody, A., Roy, S. (1999). Environmental regulation and development: A cross-country empirical analysis. The World Bank.10.1596/1813-9450-1448Search in Google Scholar

De Carvalho, F.D.A., Lechevallier, Y., De Melo, F.M. (2012). Partitioning hard clustering algorithms based on multiple dissimilarity matrices. Pattern Recognition, 45 (1), 447–464.10.1016/j.patcog.2011.05.016Search in Google Scholar

Demirgüç-Kunt, A., Levine, R. (eds.) (2004). Financial structure and economic growth: A cross-country comparison of banks, markets, and development. MIT press.Search in Google Scholar

Diday, E., Noirhomme-Fraiture, M. (eds.) (2008). Symbolic data analysis and the SODAS software. John Wiley & Sons.10.1002/9780470723562Search in Google Scholar

Dijkstra, A.G., Hanmer, L.C. (2000). Measuring socio-economic gender inequality: Toward an alternative to the UNDP gender-related development index. Feminist economics, 6 (2), 41–75.10.1080/13545700050076106Search in Google Scholar

Dudoit, S., Fridlyand, J. (2003). Bagging to improve the accuracy of a clustering procedure. Bioinformatics, 19 (9), 1090–1099.10.1093/bioinformatics/btg038Search in Google Scholar

Durand, M. (2015). The OECD better life initiative: How’s life? and the measurement of well- being. Review of Income and Wealth, 61 (1), 4–17.10.1111/roiw.12156Search in Google Scholar

Fred, A.L., Jain, A.K. (2005). Combining multiple clusterings using evidence accumulation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 6, 835–850.10.1109/TPAMI.2005.113Search in Google Scholar

Gatnar, E., Walesiak, M. (2011). Analiza danych jakościowych i symbolicznych z wykorzystaniem programu R. Warszawa: C.H. Beck.Search in Google Scholar

Ghaemi, R., Sulaiman, M.N., Ibrahim, H., Mustapha, N. (2009). A survey: clustering ensembles techniques. World Academy of Science, Engineering and Technology, 50, 636–645.Search in Google Scholar

Groenen, P., Terada, Y. (2015). Symbolic Multidimensional Scaling (No. EI 2015-15).10.1016/B978-0-08-097086-8.42167-7Search in Google Scholar

Groenen, P.J., Winsberg, S., Rodriguez, O., Diday, E. (2006). I-Scal: Multidimensional scaling of interval dissimilarities. Computational Statistics & Data Analysis, 51 (1), 360–378.10.1016/j.csda.2006.04.003Search in Google Scholar

Groenen, P.J.F., Winsberg, S., Rodriguez, O., Diday, E. (2005). SymScal: symbolic multidimensional scaling of interval dissimilarities (No. EI 2005-15). Econometric Institute Research Papers.Search in Google Scholar

Hellwig, Z. (1981). Wielowymiarowa analiza porównawcza i jej zastosowanie w badaniach wielocechowych obiektów gospodarczych. In: W. Welfe (ed.), Metody i modele ekonomiczno-matematyczne w doskonaleniu zarządzania gospodarką socjalistyczną (pp. 46–68). Warszawa: PWE.Search in Google Scholar

Hornik, K. (2005). A CLUE for CLUster ensembles. Journal of Statistical Software, 14 (12), 1–25.10.18637/jss.v014.i12Search in Google Scholar

Hsu, P.H., Tian, X., Xu, Y. (2014). Financial development and innovation: Cross-country evidence. Journal of Financial Economics, 112 (1), 116–135.10.1016/j.jfineco.2013.12.002Search in Google Scholar

Kaufman, L., Rousseeuw, P.J. (2009). Finding groups in data: an introduction to cluster analysis (Vol. 344). John Wiley & Sons.Search in Google Scholar

Ketels, C.H., Memedovic, O. (2008). From clusters to cluster-based economic development. International Journal of Technological Learning, Innovation and Development, 1 (3), 375–392.10.1504/IJTLID.2008.019979Search in Google Scholar

Leisch, F. (1999). Bagged clustering. Working Paper no. 51. Vienna University of Economic-sand Business Administration.Search in Google Scholar

Liapis, K., Rovolis, A., Galanos, C., Thalassinos, E. (2013). The Clusters of Economic Similarities between EU Countries: A View Under Recent Financial and Debt Crisis. European Research Studies, 16 (1).10.35808/ersj/380Search in Google Scholar

Magee, L., Scerri, A., James, P. (2012). Measuring social sustainability: A community-centred approach. Applied Research in Quality of Life, 7 (3), 239–261.10.1007/s11482-012-9166-xSearch in Google Scholar

Mercan, B., Goktas, D. (2011). Components of innovation ecosystems: a cross-country study. International research journal of finance and economics, 76 (16), 102–112.Search in Google Scholar

McGillivray, M. (1991). The human development index: yet another redundant composite development indicator? World Development, 19 (10), 1461–1468.10.1016/0305-750X(91)90088-YSearch in Google Scholar

Nayak, P. (2010). Human development: conceptual and measurement issues. In: P. Nayak (ed.), Growth and Human Development in North East India (pp. 3–18). New Delhi: Oxford University Press.Search in Google Scholar

Noirhomme-Fraiture, M., Brito, P. (2011). Far beyond the classical data models: symbolic data analysis. Statistical Analysis and Data Mining: the ASA Data Science Journal, 4 (2), 157–170.10.1002/sam.10112Search in Google Scholar

Pełka, M. (2017). Klasyfikacja wielomodelowa danych symbolicznych w badaniu innowacyjności krajów Unii Europejskiej. Ekonometria, 2 (56), 42–51.10.15611/ekt.2017.2.03Search in Google Scholar

Pełka, M. (2018). Analysis of Innovations in the European Union Via Ensemble Symbolic Density Clustering. Econometrics, 22 (3), 84–98.10.15611/eada.2018.3.06Search in Google Scholar

Pełka, M. (2015). An adaptation of COBWEB for symbolic data case. Statistica, 75 (3), 265–273Search in Google Scholar

Sen, A. (1999). Freedom as development. New York: Oxford Univerity Press.Search in Google Scholar

Sagar, A.D., Najam, A. (1998). The human development index: a critical review. Ecological economics, 25 (3), 249–264.10.1016/S0921-8009(97)00168-7Search in Google Scholar

Sen, A. (1994). Human Development Index: Methodology and Measurement.Search in Google Scholar

Stanton, E.A. (2007). The human development index: A history. PERI Working Papers, 85.Search in Google Scholar

Vachon, S., Mao, Z. (2008). Linking supply chain strength to sustainable development: a country-level analysis. Journal of Cleaner Production, 16 (15), 1552–1560.10.1016/j.jclepro.2008.04.012Search in Google Scholar

Verde, R. (2004). Clustering methods in symbolic data analysis. In: Classification, clustering, and data mining applications (pp. 299–317). Berlin, Heidelberg: Springer.10.1007/978-3-642-17103-1_29Search in Google Scholar

Voigt, S. (2009). The effects of competition policy on development–cross-country evidence using four new indicators. Journal of Development Studies, 45 (8), 1225–1248.10.1080/00220380902866862Search in Google Scholar

Walesiak, M. (2016). Visualization of linear ordering results for metric data with the application of multidimensional scaling. Ekonometria, 2 (52), 9–21.Search in Google Scholar

Walesiak, M. (2017a). Wizualizacja wyników porządkowania liniowego dla danych porządkowych z wykorzystaniem skalowania wielowymiarowego. Przegląd Statystyczny, 64 (1), 5–19.10.15611/ekt.2016.2.01Search in Google Scholar

Walesiak, M. (2017b). The application of multidimensional scaling to measure and assess changes in the level of social cohesion of the Lower Silesia region in the period 2005–2015. Econometrics/Ekonometria, 3 (57).10.15611/ekt.2017.3.01Search in Google Scholar

Walesiak, M., Dudek, A. (2018). The mdsOpt package for R software. Retrieved from: www.r-project.org.Search in Google Scholar

eISSN:
1898-0198
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
2 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Wirtschaftswissenschaften, Volkswirtschaft, andere