C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.22772.96641, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
Missing values in hydrometeorological time series is a commonplace and filling these values remains still a challenge. Since datasets without missing values may be a prerequisite in performing many statistical analyses, a quick and efficient gap-filling methodology is required. In this study the problem of filling sporadic gaps of time series using time-adjacent observations from the same location is investigated. The applicability of a local average (i.e., based on few neighbouring in time observations) is examined and its advantages over the commonly used sample average (i.e., using the whole dataset) are illustrated. The analysis reveals that a quick and very efficient (i.e., minimum mean squared estimation error) gap-filling is achieved by combining a strictly local average (i.e., using one observation before and one after the missing value) with the sample mean.
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Our works that reference this work:
|1.||D. Koutsoyiannis, Stochastics of Hydroclimatic Extremes - A Cool Look at Risk, Edition 2, ISBN: 978-618-85370-0-2, 346 pages, doi:10.57713/kallipos-1, Kallipos Open Academic Editions, Athens, 2022.|
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