Simple imputation-based online predictors (Yule-Walker and Kalman filter) outperformed a sampling-based no-imputation method, AERR, across synthetic and real time series with missing values.
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Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation
Simple imputation-based online predictors (Yule-Walker and Kalman filter) outperformed a sampling-based no-imputation method, AERR, across synthetic and real time series with missing values.