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Estimating the covariance function with functional data.

Sik-Yum Lee·Wenyang Zhang·Xin-Yuan Song
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Abstract

This paper describes a two-step procedure for estimating the covariance function and its eigenvalues and eigenfunctions in situations where the data are curves or functions. The first step produces initial estimates of eigenfunctions using a standard principal components analysis. At the second step, these initial estimates are smoothed via local polynomial fitting, with the bandwidth in the kernel function being selected by a data-driven procedure. The results of a simulation study and three real examples are presented to illustrate the performance of the proposed methodology.

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Sik-Yum Lee, Wenyang Zhang, Xin-Yuan Song. 2002. Estimating the covariance function with functional data.. https://doi.org/10.1348/000711002760554570

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