PL EN


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
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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