On local times, density estimation and classification rules for functional data

Pamela Nerina Llop, Liliana Forzani, Ricardo Fraiman

Abstract


In this paper we define a $\sqrt{n}$-consistent nonparametric density estimator for functional data. Under mild conditions we obtain strong consistency, strong orders of convergence and derive the asymptotic distribution of the estimator. We propose a nonparametric classification rule based on local times (occupation measure) and include some simulations studies

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