Forecasting time series by functional PCA. Discussion of several weighted approaches
type: Item
instance of: scholarly article
title: Forecasting time series by functional PCA. Discussion of several weighted approaches
zbMATH Open document ID: 0941.62102
published in: Computational Statistics
publication date: 2000-05-24T00:00:00Z
review text: The authors study continuous time series that have been observed only at discrete time points. A weighted estimation of the principal components is applied to forecast such time series. Several approaches are used to model and forecast a simulated narrow-band process by using different types of weighting functions. The model is compared with multivariate principal component regression models.
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62H25
zbMATH DE Number: 1452448
zbMATH Keywords: time series
zbMATH Keywords: principal components
zbMATH Keywords: orthogonal expansions
zbMATH Keywords: weighted functional estimation
zbMATH Keywords: interpolating splines
author: Ana M. Aguilera
author: Francisco A. Ocaña
author: Mariano J. Valderrama
MaRDI profile type: Publication
full work available at URL: s001800050025
OpenAlex ID: W2056977899
DOI: 10.1007/S001800050025
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description: scientific article; zbMATH DE number 1452448