IngentaConnect Functional quasi-likelihood regression models with smooth random ...

Authors: Chiou J-M.¹; Müller H-G.²; Wang J-L.²

Source: Journal of the Royal Statistical Society: Series B (Statistical Methodology), Volume 65, Number 2, May 2003 , pp. 405-423(19)

Publisher: Blackwell Publishing

Abstract:

Summary.

We propose a class of semiparametric functional regression models to describe the influence of vector-valued covariates on a sample of response curves. Each observed curve is viewed as the realization of a random process, composed of an overall mean function and random components. The finite dimensional covariates influence the random components of the eigenfunction expansion through single-index models that include unknown smooth link and variance functions. The parametric components of the single-index models are estimated via quasi-score estimating equations with link and variance functions being estimated nonparametrically. We obtain several basic asymptotic results. The functional regression models proposed are illustrated with the analysis of a data set consisting of egg laying curves for 1000 female Mediterranean fruit-flies (medflies).

Keywords: Estimating equations; Functional data analysis; Functional regression; Principal components; Semiparametric quasi-likelihood regression; Single-index model; Smoothing

Document Type: Research article

DOI: 10.1111/1467-9868.00393

Affiliations: 1: National Health Research Institutes, Taipei, Taiwan 2: University of California, Davis, USA

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Functional quasi-likelihood regression models with smooth random effects