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High-dimensional functional time series forecasting, in Functional Statistics and Related Fields

Gao, Yuan; Shang, Hanlin; Yang, Yanrong

Description

In this paper, we address the problem of forecasting high-dimensional functional time series through a two-fold dimension reduction procedure. Dynamic functional principal component analysis is applied to reduce each infinite-dimension functional time series to a vector. We use factor model as a further dimension reduction technique so that only a small number of latent factors are preserved. Simple time series models can be used to forecast the factors and forecast of the functions can be...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Book chapter
URI: http://hdl.handle.net/1885/219725
Book Title: Functional Statistics and Related Fields
DOI: 10.1007/978-3-319-55846-2_17

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