SFB 303 Discussion Paper No. A - 351
Author: Kneip, Alois
Title: Nonparametric Estimation of Common Regressors for Similar Curve Data
Abstract: The paper is concerned with data from a collection of different, but
related regression curves. In statistical practice analysis of such data is
most frequently based on low dimensional linear models. It is then assumed
that each regression curve is a linear combination of a small number L of
common functions. In this paper the assumption of a prespecified model is
dropped. A nonparametric method is presented which allows to estimate the
smallest L and corresponding functions from the data. The procedure combines
smoothing techniques with ideas related to Principal Component Analysis. An
asymptotic theory is presented which yields detailed insight into properties
of the resulting estimators. An application to household expenditure data
illustrates the approach.
Keywords: Regression, curve estimation, linear models, model selection, principal
components
JEL-Classification-Number:
Creation-Date: November 1991
Unfortunately this paper is not available. Please order a hardcopy via e-mail.
SFB 303 Homepage
12.05.1998, Webmaster