Nonparametric regression for locally stationary functional time series

Autor:	Kurisu, Daisuke
Rok vydání:	2021
Předmět:	Mathematics - Statistics Theory
Druh dokumentu:	Working Paper
Popis:	In this study, we develop an asymptotic theory of nonparametric regression for a locally stationary functional time series. First, we introduce the notion of a locally stationary functional time series (LSFTS) that takes values in a semi-metric space. Then, we propose a nonparametric model for LSFTS with a regression function that changes smoothly over time. We establish the uniform convergence rates of a class of kernel estimators, the Nadaraya-Watson (NW) estimator of the regression function, and a central limit theorem of the NW estimator. Comment: 20 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.07613 Zobrazit plný text záznamu View this record from Arxiv