Forecasting time series by functional PCA. Discussion of several weighted approaches
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.
scientific article; zbMATH DE number 1452448