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2013 | 14 | 1 | 180-189

Article title

FUNCTIONAL EXPLORATORY DATA ANALYSIS OF UNEMPLOYMENT RATE FOR VARIOUS COUNTRIES

Content

Title variants

Languages of publication

EN

Abstracts

EN
Functional exploratory techniques are applied in the analysis of an unemployment rate. The rate is smoothed into differentiable function in order to facilitate the analysis. The main aim of the analysis is assigned to find out the unemployment curves which do not follow the same pattern as that of the other ones.

Year

Volume

14

Issue

1

Pages

180-189

Physical description

Dates

published
2013

Contributors

  • Department of Econometrics and Statistics Warsaw University of Life Sciences – SGGW

References

  • Burgen E., Meyer B., and Tasci M. (2012) An Elusive Relation between Unemployment and GDP Growth: Okun’s Law. Cleveland Federal Reserve Economic Trends.
  • Cuevas A., Febrero-Bande M., Fraiman R. (2007) Robust Estimation and Clasification for Functional Data via Projction-Based Depth Notions, Computational Statistics, 22(3), 481-496.
  • Febrero-Bande M., Galeano P., Gonzales-Manteiga W. (2008) Outlier Detection in Functional Data by Depth Measures, with Application to Identity Abnormal NOx Levels, Environmetrics, 19(4), 331-345
  • Ferraty F., Vieu P. (2006) Nonparametric Functional Data Analysis, Springer Series in Statistics. Springer-Verlag, New York. Theory and practice.
  • Furmańczyk K., Jaworski S. (2012) Unemployment rate for various countries since 2005 to 2012: comparison of its level and pace using functional principal analysis. Quntitative Methods in Economics, Vol. XIII, No 2, pp. 40-47.
  • Horváth L, Kokoszka P. (2012) Inference for Functional Data with Applications, Springer Series in Statistics
  • Ramsay J.O., Silverman B. W. (2005) Functional Data Analysis. Second Edition, Springer, NY.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-49d09d50-ff08-45a3-a0d5-bef5f2c4454f
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