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

published in

publication date

  • January 2020

issue

  • 3

volume

  • 29

International Standard Serial Number (ISSN)

  • 1133-0686

Electronic International Standard Serial Number (EISSN)

  • 1863-8260

abstract

  • (copyright) 2019, Sociedad de Estadística e Investigación Operativa.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.

keywords

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