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Rank-based tests for autoregressive against bilinear serial dependence 

Authors: Youssef Benghabrit a; Marc Hallin - ab
Affiliations:   a Ecole Mohammadia d'Ingeacutenieurs Rabat, Morocco
b Institut de Statistique and Deacutepartement de Matheacutematique, Universiteacute Libre de Bruxelles Brussels, Belgium
DOI: 10.1080/10485259608832674
Publication Frequency: 8 issues per year
Published in: journal Journal of Nonparametric Statistics, Volume 6, Issue 2 & 3 1996 , pages 253 - 272
Formats available: PDF (English)
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Abstract

Opumal (signed and unsigned) rank-based procedures are derived for the problem of testing autoregiessive AR(l) dependence, with unspecified autoregressive parameter and innovation density, against firstorder diagonal bilinear dependence, The proposed test statistics rely on rank-based versions of the residual spectrum and bispectrum. The resulting tests are asymptotically invariant, hence asymptotically distribution-free, and locally asymptotically most powerful. Their local asymptotic powers and asymptotic relative efficiencies with respect to the Gaussian Lagrange multiplier procedure of Saikkonen and Luukkonen (1988) are provided explicitly.
Keywords: time series; bilinear model; bispectrum; test of linearity; rank test; aligned ranks
AMS 1980 Subject classification: 62M10; 62G10; 62F05
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