Print Email Facebook Twitter Interpolation in Time Series Title Interpolation in Time Series: An Introductive Overview of Existing Methods, Their Performance Criteria and Uncertainty Assessment Author Lepot, M.J. (TU Delft Sanitary Engineering) Aubin, Jean Baptiste (Université de Lyon) Clemens, F.H.L.R. (TU Delft Sanitary Engineering; Deltares) Date 2017 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. Subject comparisonreviewuncertaintymethodsinterpolationcriteriaOA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:a1be9972-78e5-4e18-8a26-a27a7582ee2a DOI https://doi.org/10.3390/w9100796 ISSN 2073-4441 Source Water, 9 (10) Part of collection Institutional Repository Document type journal article Rights © 2017 M.J. Lepot, Jean Baptiste Aubin, F.H.L.R. Clemens Files PDF water_09_00796.pdf 715.45 KB Close viewer /islandora/object/uuid:a1be9972-78e5-4e18-8a26-a27a7582ee2a/datastream/OBJ/view