A goodness-of-fit test for regression models with spatially correlated errors Articles uri icon

published in

publication date

  • January 2020

start page

  • 728

end page

  • 749

issue

  • 3

volume

  • 29

International Standard Serial Number (ISSN)

  • 1133-0686

Electronic International Standard Serial Number (EISSN)

  • 1863-8260

abstract

  • The problem of assessing a parametric regression model in the presence of spatial
    correlation is addressed in this work. For that purpose, a goodness-of-fit test based
    on a L2 -distance comparing a parametric and nonparametric regression estimators is
    proposed. Asymptotic properties of the test statistic, both under the null hypothesis and
    under local alternatives, are derived. Additionally, a bootstrap procedure is designed to
    calibrate the test in practice. Finite sample performance of the test is analyzed through
    a simulation study, and its applicability is illustrated using a real data example.

subjects

  • Mathematics
  • Statistics

keywords

  • bootstrap; least squares; local linear regression; model checking; spatial correlation