What is it about?
We suggest a systematic set to detect sustainable trends in functional time series.
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Why is it important?
Big datasets are often very noisy and due to their complex structure they are very difficult to extract trends i.e. non-noisy information. The suggested filter contributes to detecting trends in such functional time series.
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This page is a summary of: On the functional Hodrick–Prescott filter with non-compact operators, Random Operators and Stochastic Equations, January 2016, De Gruyter,
DOI: 10.1515/rose-2016-0003.
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