Functional Quasi-Likelihood Regression Models with Smooth Random Effects
Journal
Journal of the Royal Statistical Society Series B: Statistical Methodology
Journal Volume
65
Journal Issue
2
Start Page
405-423
ISSN
1369-7412
1467-9868
Date Issued
2003-04-25
Author(s)
Abstract
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).
Publisher
Oxford University Press (OUP)
Type
journal article