On the estimation of locally stationary functional time series

Autor:	Kurisu, Daisuke
Rok vydání:	2021
Předmět:	Mathematics - Statistics Theory Statistics - Methodology
Druh dokumentu:	Working Paper
Popis:	This study develops an asymptotic theory for estimating the time-varying characteristics of locally stationary functional time series (LSFTS). We investigate a kernel-based method to estimate the time-varying covariance operator and the time-varying mean function of an LSFTS. In particular, we derive the convergence rate of the kernel estimator of the covariance operator and associated eigenvalue and eigenfunctions and establish a central limit theorem for the kernel-based locally weighted sample mean. As applications of our results, we discuss methods for testing the equality of time-varying mean functions in two functional samples. Comment: 36 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.11873 Zobrazit plný text záznamu View this record from Arxiv