Ayuda
Ir al contenido

Dialnet


Copula-Based Regression Estimation and Inference

  • Autores: Hohsuk Noh, Anouar El Ghouch, Taoufik Bouezmarni
  • Localización: Journal of the American Statistical Association, ISSN 0162-1459, Vol. 108, Nº 502, 2013, págs. 676-688
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • We investigate a new approach to estimating a regression function based on copulas. The main idea behind this approach is to write the regression function in terms of a copula and marginal distributions. Once the copula and the marginal distributions are estimated, we use the plug-in method to construct our new estimator. Because various methods are available in the literature for estimating both a copula and a distribution, this idea provides a rich and flexible family of regression estimators. We provide some asymptotic results related to this copula-based regression modeling when the copula is estimated via profile likelihood and the marginals are estimated nonparametrically. We also study the finite sample performance of the estimator and illustrate its usefulness by analyzing data from air pollution studies.


Fundación Dialnet

Dialnet Plus

  • Más información sobre Dialnet Plus

Opciones de compartir

Opciones de entorno