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Estimation of Long Memory Linear Processes

Abstract

This paper studies asymptotic properties of the minimum distance Hellinger estimates for a stationaryultivariate linear gaussien long range dependent process of the form , where is a sequence of strictly stationary d-dimensional associated random vectors with E(Zt)= 0 and and {Au} is a sequence of coefficient matrices with and . By means of the properties of the kernel density estimate, the minimum istance Hellinger of this class are shown to be consistent, asymptotically normal and robust.

Ichaou Mounirou

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