FEDS Paper: Missing Data Substitution for Enhanced Robust Filtering and Forecasting in Linear State-Space Models

Dobrislav Dobrev and Paweł J. SzerszeńReplacing faulty measurements with missing values can suppress outlier-induced distortions in state-space inference. We therefore put forward two complementary methods for enhanced outlier-robust filtering and forecasting: supervised missing data substitution (MD) upon exceeding a Huber threshold, and unsupervised missing data substitution via exogenous randomization (RMDX).