Forecasting functional time series using weighted likelihood methodology

Volume: 89, Issue: 16, Pages: 3046 - 3060
Published: Aug 1, 2019
Abstract
Functional time series whose sample elements are recorded sequentially over time are frequently encountered with increasing technology. Recent studies have shown that analyzing and forecasting of functional time series can be performed easily using functional principal component analysis and existing univariate/multivariate time series models. However, the forecasting performance of such functional time series models may be affected by the...
Paper Details
Title
Forecasting functional time series using weighted likelihood methodology
Published Date
Aug 1, 2019
Volume
89
Issue
16
Pages
3046 - 3060
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