Nonparametric Lag Selection for Additive Models based on the Smooth Backfitting Estimator ()
ABSTRACT
This paper proposes a nonparametric FPE-like procedure based on the smooth backfitting estimator when the additive structure is a priori known. This procedure can be expected to perform well because of its well-known finite sample performance of the smooth backfitting estimator. Consistency of our procedure is established under very general conditions, including heteroskedasticity.
Share and Cite:
Guo, Z. , Cao, L. and He, Y. (2011) Nonparametric Lag Selection for Additive Models based on the Smooth Backfitting Estimator.
Theoretical Economics Letters,
1, 15-17. doi:
10.4236/tel.2011.12004.
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