PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Efficient semi-parametric estimation of the periods in a superposition of periodic functions with unknown shape
Elisabeth Gassiat and Celine Levy-Leduc
Journal of Time Series Analysis Volume 27, Number 6, pp. 877-910, 2006.

Abstract

We consider the estimation of the periods from a sum of periodic functions of unknown shape corrupted by Gaussian white noise. In the case of a single periodic signal, we propose a consistent and asymptotically efficient semiparametric estimator of the period. We then study the case of a sum of two periodic signals of unknown shape with different periods. For a large class of signals, we propose semiparametric estimators of the two periods that are consistent and asymptotically Gaussian.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:671
Deposited By:Elisabeth Gassiat
Deposited On:29 December 2004