Specification Tests for the Distribution of Errors in Nonparametric Regression: A Martingale Approach Articles uri icon

authors

  • MORA LOPEZ, JUAN
  • PEREZ ALONSO, ALICIA

publication date

  • June 2009

start page

  • 441

end page

  • 452

issue

  • 4

volume

  • 21

International Standard Serial Number (ISSN)

  • 1048-5252

Electronic International Standard Serial Number (EISSN)

  • 1029-0311

abstract

  • We discuss how to test whether the distribution of regression errors belongs to a parametric family of continuous distribution functions, making no parametric assumption about the conditional mean or the conditional variance in the regression model. We propose using test statistics that are based on a martingale transform of the estimated empirical process. We prove that these statistics are asymptotically distribution-free, and two Monte Carlo experiments show that they work reasonably well in practice.