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Statistica Sinica 6(1996), 147-169


LOCALLY ASYMPTOTICALLY OPTIMAL TESTS FOR

AUTOREGRESSIVE AGAINST BILINEAR

SERIAL DEPENDENCE


Youssef Benghabrit and Marc Hallin


Ecole Mohammadia d'Ingénieurs and Université Libre de Bruxelles


Abstract: Locally asymptotically most stringent tests for autoregressive against diagonal bilinear time series models are derived. A (restricted) local asymptotic normality property is therefore established for bilinear processes in the vicinity of linear autoregressive ones. The behaviour of the bispectrum under local alternatives of bilinear dependence shows the danger of misinterpreting skewness or kurtosis effects for nonlinearities. The proposed test statistic is a generalization of the Gaussian Lagrange multip lier statistic considered by Saikkonen and Luukkonen (1988), and is expressed as a closed-form function of the estimated residual spectrum and bispectrum. Its local power is explicitly provided. The local power of the Lagrange multiplier test follows as a particular case.



Key words and phrases: Time series, bilinear model, local asymptotic normality, bispectrum.



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