The Annals of Statistics

Functional single index models for longitudinal data

Ci-Ren Jiang and Jane-Ling Wang

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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 $\sqrt{n}$-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.

Article information

Ann. Statist., Volume 39, Number 1 (2011), 362-388.

First available in Project Euclid: 3 December 2010

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62G08: Nonparametric regression 62G05: Estimation
Secondary: 62G20: Asymptotic properties

Asymptotic theory cross-validation dimension reduction functional data MAVE smoothing


Jiang, Ci-Ren; Wang, Jane-Ling. Functional single index models for longitudinal data. Ann. Statist. 39 (2011), no. 1, 362--388. doi:10.1214/10-AOS845.

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