Sieve bootstrap for functional time series

DOI10.1214/17-AOS1667zbMath1420.62392arXiv1609.06029OpenAlexW2963256730MaRDI QIDQ1990591

Efstathios Paparoditis

Publication date: 25 October 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1609.06029

zbMATH Keywords

bootstrapFourier transformprincipal componentsspectral density operatorKarhunen-Loeve expansian

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Nonparametric statistical resampling methods (62G09)

Related Items (11)

Principal Component Analysis of Spatially Indexed Functions ⋮ Sieve bootstrapping the memory parameter in long-range dependent stationary functional time series ⋮ Bootstrap Prediction Bands for Functional Time Series ⋮ Bootstrap methods for stationary functional time series ⋮ Functional GARCH models: the quasi-likelihood approach and its applications ⋮ A bootstrap-based KPSS test for functional time series ⋮ Nonlinear autoregressive sieve bootstrap based on extreme learning machines ⋮ Double bootstrapping for visualizing the distribution of descriptive statistics of functional data ⋮ Bootstrapping covariance operators of functional time series ⋮ Testing equality of spectral density operators for functional processes ⋮ Moving block and tapered block bootstrap for functional time series with an application to the \(K\)-sample mean problem

Uses Software

• freqdom.fda

Cites Work

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