Nonparametric Estimation of Variance Function for Functional Data

Details Nonparametric Estimation of Variance Function for Functional Data Nonparametric Estimation of Variance Function for Functional Data

2008-12-14

arxiv.org/abs/0812.2628v1

Statistics

Methodology

Scientific paper

This article investigates nonparametric estimation of variance functions for functional data when the mean function is unknown. We obtain asymptotic results for the kernel estimator based on squared residuals. Similar to the finite dimensional case, our asymptotic result shows the smoothness of the unknown mean function has an effect on the rate of convergence. Our simulaton studies demonstrate that estimator based on residuals performs much better than that based on conditional second moment of the responses.

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