Functional linear model

In this paper, we study a regression model in which explanatory variables are sampling points of a continuous-time process. We propose an estimator of regression by means of a Functional Principal Component Analysis analogous to the one introduced by Bosq [(1991) NATO, ASI Series, pp. 509-529] in the case of Hilbertian AR processes. Both convergence in probability and almost sure convergence of this estimator are stated.

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Year of publication:	1999
Authors:	Cardot, Hervé ; Ferraty, Frédéric ; Sarda, Pascal
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 45.1999, 1, p. 11-22
Publisher:	Elsevier
Keywords:	Functional linear model Functional data analysis Hilbert spaces Convergence

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005074625