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Independent Component Analysis Via Copula Techniques

Author

Listed:
  • Ray-Bing Chen
  • Meihui Guo
  • Wolfgang Härdle
  • Shih-Feng Huang

Abstract

Independent component analysis (ICA) is a modern factor analysis tool de- veloped in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then independent components are found by optimizing the copula parameters. Based on this idea, we propose the COPICA method for searching independent components. We illustrate this method using several blind source separation examples, which are mathematically equivalent to ICA problems. Finally performances of our method and FastICA are compared to explore the advantages of this method.

Suggested Citation

  • Ray-Bing Chen & Meihui Guo & Wolfgang Härdle & Shih-Feng Huang, 2008. "Independent Component Analysis Via Copula Techniques," SFB 649 Discussion Papers SFB649DP2008-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    • Handle: RePEc:hum:wpaper:sfb649dp2008-004
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    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2008-004.pdf
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    References listed on IDEAS

    as
    1. Rafael Schmidt, 2002. "Tail dependence for elliptically contoured distributions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 55(2), pages 301-327, May.
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    Cited by:

    1. Kumiega, Andrew & Neururer, Thaddeus & Van Vliet, Ben, 2011. "Independent component analysis for realized volatility: Analysis of the stock market crash of 2008," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 292-302, June.

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    More about this item

    Keywords

    Blind source separation; Canonical maximum likelihood method; Givens rotation matrix; Signal/noise ratio; Simulated annealing algorithm;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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