Skip to Main content Skip to Navigation
Reports

A Nonparametric Goodness-of-fit Test for a Class of Parametric Autoregressive Models

Joseph Ngatchou Wandji 1
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : We derive a nonparametric test for discriminating between generalized autoregressive models. This test is based on a suitably normalized sum of residuals. The null distribution and the power of the test under both fixed and a sequence of local alternatives are studied under mild stationarity and $\alpha$--mixing conditions. This procedure can be applied to testing linear models against nonlinear models or certain nonlinear models against others. Numerical simulations show that the proposed test is powerful against most of the alternatives considered.
Document type :
Reports
Complete list of metadata

https://hal.inria.fr/inria-00073627
Contributor : Rapport de Recherche Inria <>
Submitted on : Wednesday, May 24, 2006 - 1:22:18 PM
Last modification on : Monday, February 10, 2020 - 4:36:45 PM
Long-term archiving on: : Sunday, April 4, 2010 - 11:52:22 PM

Identifiers

  • HAL Id : inria-00073627, version 1

Collections

Citation

Joseph Ngatchou Wandji. A Nonparametric Goodness-of-fit Test for a Class of Parametric Autoregressive Models. RR-3065, INRIA. 1996. ⟨inria-00073627⟩

Share

Metrics

Record views

368

Files downloads

499