Interpolation in Time Series
An Introductive Overview of Existing Methods, Their Performance Criteria and Uncertainty Assessment
Mathieu Lepot (TU Delft - Sanitary Engineering)
Jean Baptiste Aubin (Université de Lyon)
F. Clemens (TU Delft - Sanitary Engineering, Deltares)
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Abstract
A thorough review has been performed on interpolation methods to fill gaps in time-series, efficiency criteria, and uncertainty quantifications. On one hand, there are numerous available methods: interpolation, regression, autoregressive, machine learning methods, etc. On the other hand, there are many methods and criteria to estimate efficiencies of these methods, but uncertainties on the interpolated values are rarely calculated. Furthermore, while they are estimated according to standard methods, the prediction uncertainty is not taken into account: a discussion is thus presented on the uncertainty estimation of interpolated/extrapolated data. Finally, some suggestions for further research and a new method are proposed.
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