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

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

Open Access
|Dec 2019

References

  1. 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.
  2. 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).
  3. Baker, B. (2011). World development: An essential text. New Internationalist.
  4. Bates, W. (2009). Gross national happiness. Asian-Pacific Economic Literature, 23 (2), 1–16.10.1111/j.1467-8411.2009.01235.x
  5. Bock, H.H., Diday, E. (eds.) (2012). Analysis of symbolic data: exploratory methods for extracting statistical information from complex data. Springer Science & Business Media.
  6. Billard, L., Diday, E. (2006). Symbolic Data Analysis: Conceptual Statistics and Data Mining John Wiley.10.1002/9780470090183
  7. 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_231
  8. Brito, P. (1995). Symbolic objects: order structure and pyramidal clustering. Annals of Operations Research, 55 (2), 277–297.10.1007/BF02030863
  9. Dasgupta, S., Wheeler, D., Mody, A., Roy, S. (1999). Environmental regulation and development: A cross-country empirical analysis. The World Bank.10.1596/1813-9450-1448
  10. 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.2011.05.016
  11. Demirgüç-Kunt, A., Levine, R. (eds.) (2004). Financial structure and economic growth: A cross-country comparison of banks, markets, and development. MIT press.
  12. Diday, E., Noirhomme-Fraiture, M. (eds.) (2008). Symbolic data analysis and the SODAS software. John Wiley & Sons.10.1002/9780470723562
  13. 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), 41–75.10.1080/13545700050076106
  14. Dudoit, S., Fridlyand, J. (2003). Bagging to improve the accuracy of a clustering procedure. Bioinformatics, 19 (9), 1090–1099.10.1093/bioinformatics/btg038
  15. 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.12156
  16. 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.2005.113
  17. Gatnar, E., Walesiak, M. (2011). Analiza danych jakościowych i symbolicznych z wykorzystaniem programu R. Warszawa: C.H. Beck.
  18. 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.
  19. Groenen, P., Terada, Y. (2015). Symbolic Multidimensional Scaling (No. EI 2015-15).10.1016/B978-0-08-097086-8.42167-7
  20. 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.2006.04.003
  21. 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.
  22. 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.
  23. Hornik, K. (2005). A CLUE for CLUster ensembles. Journal of Statistical Software, 14 (12), 1–25.10.18637/jss.v014.i12
  24. 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.2013.12.002
  25. Kaufman, L., Rousseeuw, P.J. (2009). Finding groups in data: an introduction to cluster analysis (Vol. 344). John Wiley & Sons.
  26. 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.2008.019979
  27. Leisch, F. (1999). Bagged clustering. Working Paper no. 51. Vienna University of Economic-sand Business Administration.
  28. 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/380
  29. 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-x
  30. Mercan, B., Goktas, D. (2011). Components of innovation ecosystems: a cross-country study. International research journal of finance and economics, 76 (16), 102–112.
  31. 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-Y
  32. 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.
  33. 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.10112
  34. Pełka, M. (2017). Klasyfikacja wielomodelowa danych symbolicznych w badaniu innowacyjności krajów Unii Europejskiej. Ekonometria, 2 (56), 42–51.10.15611/ekt.2017.2.03
  35. Pełka, M. (2018). Analysis of Innovations in the European Union Via Ensemble Symbolic Density Clustering. Econometrics, 22 (3), 84–98.10.15611/eada.2018.3.06
  36. Pełka, M. (2015). An adaptation of COBWEB for symbolic data case. Statistica, 75 (3), 265–273
  37. Sen, A. (1999). Freedom as development. New York: Oxford Univerity Press.
  38. Sagar, A.D., Najam, A. (1998). The human development index: a critical review. Ecological economics, 25 (3), 249–264.10.1016/S0921-8009(97)00168-7
  39. Sen, A. (1994). Human Development Index: Methodology and Measurement.
  40. Stanton, E.A. (2007). The human development index: A history. PERI Working Papers, 85.
  41. 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.2008.04.012
  42. 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_29
  43. Voigt, S. (2009). The effects of competition policy on development–cross-country evidence using four new indicators. Journal of Development Studies, 45 (8), 1225–1248.10.1080/00220380902866862
  44. Walesiak, M. (2016). Visualization of linear ordering results for metric data with the application of multidimensional scaling. Ekonometria, 2 (52), 9–21.
  45. Walesiak, M. (2017a). Wizualizacja wyników porządkowania liniowego dla danych porządkowych z wykorzystaniem skalowania wielowymiarowego. Przegląd Statystyczny, 64 (1), 5–19.10.15611/ekt.2016.2.01
  46. 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.2017.3.01
  47. Walesiak, M., Dudek, A. (2018). The mdsOpt package for R software. Retrieved from: www.r-project.org.
DOI: https://doi.org/10.2478/foli-2019-0017 | Journal eISSN: 1898-0198 | Journal ISSN: 1730-4237
Language: English
Page range: 117 - 133
Submitted on: Nov 13, 2018
Accepted on: Oct 15, 2019
Published on: Dec 26, 2019
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year

© 2019 Marcin Pełka, published by Sciendo
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