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Additive Nonlinear ARX Time Series and Projection Estimates

Published online by Cambridge University Press:  11 February 2009

Elias Masry
Affiliation:
University of California at San Diego
Dag Tjøstheim
Affiliation:
University of Bergen

Abstract

We propose projections as means of identifying and estimating the components (endogenous and exogenous) of an additive nonlinear ARX model. The estimates are nonparametric in nature and involve averaging of kernel-type estimates. Such estimates have recently been treated informally in a univariate time series situation. Here we extend the scope to nonlinear ARX models and present a rigorous theory, including the derivation of asymptotic normality for the projection estimates under a precise set of regularity conditions.

Type
Articles
Copyright
Copyright © Cambridge University Press 1997

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