Nonparametric Regression with Serially Correlated Errors

Jan G. Gooijer and Ali Gannoun
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Ali Gannoun: Irène Larramendy, Université de Montpellier II

No 99-063/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Motivated by the problem of setting prediction intervals in time seriesanalysis, this investigation is concerned with recovering a regression functionm(X_t) on the basis of noisy observations taking at random design pointsX_t.It is presumed that the corresponding observations are corrupted by additiveserially correlated noise and that the noise is, in fact, induced by a generallinear process. The main result of this study is that, under some reasonableconditions, the nonparametric kernel estimator of m(x)(/i) is asymptoticallynormally distributed. Using this result, we construct confidence bands form(x).Simulations will be conducted to assess the performance of these bands infinite-sample situations

Date: 1999-08-17
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:19990063

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