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stat.ME2026
Model-agnostic noise reduction for high-dimensional time series data
Bram Wouters, Cees Diks
We develop a model-agnostic framework for noise reduction in high-dimensional time series that explicitly targets optimal recovery of a low-dimensional latent dynamic component con…
stat.ME2023
Noise reduction for functional time series
Cees Diks, Bram Wouters
A novel method for noise reduction in the setting of curve time series with error contamination is proposed, based on extending the framework of functional principal component anal…