Record link: 
http://hdl.handle.net/20.500.12708/192288
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Title: 
Improving Forecasts for Time Series of Different Lengths by "Averaging", with Application to Food Demand Prediction
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Citation: 
Neubauer, L., & Filzmoser, P. (2023, March 7). Improving Forecasts for Time Series of Different Lengths by “Averaging”, with Application to Food Demand Prediction [Conference Presentation]. 16th German Probability and Statistics Days Essen 2023, Essen, Germany.
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Publication Type: 
Presentation - Conference Presentation
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Language: 
English
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Authors: 
Neubauer, Lukas 
Filzmoser, Peter 
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Organisational Unit: 
E105-06 - Forschungsbereich Computational Statistics 
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Date (published): 
7-Mar-2023
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Event name: 
16th German Probability and Statistics Days Essen 2023 
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Event date: 
7-Mar-2023 - 10-Mar-2023
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Event place: 
Essen, Germany
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Keywords: 
Forecasting; Short Time Series; Dynamic Time Warping; k-Nearest Neighbors
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Research Areas: 
Mathematical Methods in Economics: 50%
Mathematical and Algorithmic Foundations: 50%
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Science Branch: 
1020 - Informatik: 10%
5020 - Wirtschaftswissenschaften: 20%
1010 - Mathematik: 70%
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Appears in Collections:
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