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Found 2 papers, 2 papers with code
On projection methods for functional time series forecasting
The second one is based on a selection of curves, termed \emph{the curve envelope}, that aims to be representative in shape and magnitude of the most recent functional observation, either a whole curve or the observed part of a partially observed curve.
Localization processes for functional data analysis
We propose an alternative to $k$-nearest neighbors for functional data whereby the approximating neighboring curves are piecewise functions built from a functional sample.
Methodology Applications
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