Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2011 | 6 | 1 | 133-142

Article title

Application of Kullback-Leibler Relative Entropy for Studies on the Divergence of Household Expenditures Structures

Authors

Title variants

Languages of publication

EN

Abstracts

EN
The paper proposes the possibility of employing the methods defined on the grounds of the information theory to research on socioeconomic phenomena. The presented measures are Shannon's entropy and Kullback-Leibler relative entropy (divergence) applied for quantification of the degree of concentration of structures and the degree of divergence between structures analyzed in the dynamic approach respectively. The paper presents studies on the degree of divergence between structures of average monthly per capita expenditures in households in Poland during the years 2000-2008.

Year

Volume

6

Issue

1

Pages

133-142

Physical description

Dates

published
2011-06-30

Contributors

  • Chair of Quantitative Methods, University of Warmia and Mazury in Olsztyn

References

  • Asadi M., Ebrahimi N., Soofi E.S. 2005. Dynamic generalized information measures. Statistics & Probability Letters, 71: 85-98.
  • Budżety gospodarstw domowych w 2008 roku. 2009. Informacje i opracowania statystyczne, GUS, Warszawa.
  • Cavanaugh J. 1999. A large-sample selection criterion based on Kullback's symmetric divergence. Statistics & Probability Letters, 42: 333-343.
  • Dhillon I.S., Mallele S., Kumar R. 2003. A divisive information - theoretic feature clustering algorithm for text classification. Journal of Machine Learning Research, 3: 1265- 1287.
  • Hung W.L., Yang M.S. 2007. On the J-divergence of intuitionistic fuzzy seta with its application to pattern recognition, Information Sciences 178: 1641-1650.
  • Lavenda B.H. 2005. Mean Entropies. Open System Infor. Dyn., 12: 289-302.
  • Młodak A. 2006. Analiza taksonomiczna w statystyce regionalnej. Wyd. Dyfin, Warszawa.
  • Nowak E. 1990. Metody taksonomiczne w klasyfikacji obiektów społeczno-gospodarczych. PWE, Warszawa.
  • Piłatowska M. 2009. Prognozy kombinowane z wykorzystaniem wag Akaike'a. Acta Universitatis Nicolai Copernici. Ekonomia, XXXIX: 51- 62.
  • Przybyszewski R., Wędrowska E. 2005. Algorytmiczna teoria entropii. Przegląd Statystyczny, 2(52): 85- 102.
  • Taksonomia struktur w badaniach regionalnych. 1998. Red. D. Strahl. Wyd. Akademii Ekonomicznej we Wrocławiu, Wrocław.
  • Wędrowska E. 2010. Classification of objects on the base of the expected information value. Olsztyn Economic Journal, 5(1): 78-89.
  • Zhang Q-S, Jiang Y-J. 2008. A note on information entropy measures for vague sets and its applications. Information Sciences, 178: 4184-4191.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-ddff77fe-cb9d-482c-9e0c-fb81ef784ff7
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.