Functional single index models for longitudinal data
Ci-Ren Jiang and Jane-Ling Wang
Source: Ann. Statist. Volume 39, Number 1
(2011), 362-388.
Abstract
A new single-index model that reflects the time-dynamic effects of the single index is proposed for longitudinal and functional response data, possibly measured with errors, for both longitudinal and time-invariant covariates. With appropriate initial estimates of the parametric index, the proposed estimator is shown to be -consistent and asymptotically normally distributed. We also address the nonparametric estimation of regression functions and provide estimates with optimal convergence rates. One advantage of the new approach is that the same bandwidth is used to estimate both the nonparametric mean function and the parameter in the index. The finite-sample performance for the proposed procedure is studied numerically.
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Keywords: Asymptotic theory; cross-validation; dimension reduction; functional data; MAVE; smoothing
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Permanent link to this document: http://projecteuclid.org/euclid.aos/1291388379
Digital Object Identifier: doi:10.1214/10-AOS845
Zentralblatt MATH identifier: 05874499
Mathematical Reviews number (MathSciNet): MR2797850
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