Supercritical Pitchfork Bifurcation in Implicit Regression Modeling

  • Authors:
  • Stan Lipovetsky

  • Affiliations:
  • GfK Custom Research North America, USA

  • Venue:
  • International Journal of Artificial Life Research
  • Year:
  • 2010

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Abstract

Chaotic systems have been widely studied for description and explanation of various observed phenomena. The problem of statistical modeling for messy data can be attempted using the so called Supercritical Pitchfork Bifurcation (SPB) approach. This work considers the possibility of applying SPB technique to regression modeling of the implicit functions. Theoretical and practical advantages of SPB regression are discussed with an example from marketing research data on advertising in the car industry. Results are very promising, which can help in modeling, analysis, interpretation, and lead to understanding of the real world data.