Skip to main content

Restricted likelihood ratio lack-of-fit tests using mixed spline models

Buy Article:

$43.00 plus tax (Refund Policy)

Summary. 

Penalized regression spline models afford a simple mixed model representation in which variance components control the degree of non-linearity in the smooth function estimates. This motivates the study of lack-of-fit tests based on the restricted maximum likelihood ratio statistic which tests whether variance components are 0 against the alternative of taking on positive values. For this one-sided testing problem a further complication is that the variance component belongs to the boundary of the parameter space under the null hypothesis. Conditions are obtained on the design of the regression spline models under which asymptotic distribution theory applies, and finite sample approximations to the asymptotic distribution are provided. Test statistics are studied for simple as well as multiple-regression models.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Boundary hypothesis; Lack of fit; Likelihood ratio test; Mixed model; Regression spline model; Restricted maximum likelihood

Document Type: Research Article

Affiliations: Texas A&M University, College Station, USA, and Université catholique de Louvain, Louvain-la-Neuve, Belgium

Publication date: 2004-11-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more