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Copula-based piecewise regression

In: Copulas and Dependence Models with Applications

Author

Listed:
  • Arturo Erdely

    (Universidad Nacional Autónoma de México, Facultad de Estudios Superiores Acatlán)

Abstract

Most common parametric families of copulas are totally ordered, and in many cases they are also positively or negatively regression dependent and therefore they lead to monotone regression functions, which makes them not suitable for dependence relationships that imply or suggest a non-monotone regression function. A gluing copula approach is proposed to decompose the underlying copula into totally ordered copulas that once combined may lead to a non-monotone regression function.

Suggested Citation

  • Arturo Erdely, 2017. "Copula-based piecewise regression," Springer Books, in: Manuel Úbeda Flores & Enrique de Amo Artero & Fabrizio Durante & Juan Fernández Sánchez (ed.), Copulas and Dependence Models with Applications, chapter 0, pages 69-81, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-64221-5_5
    DOI: 10.1007/978-3-319-64221-5_5
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