The UCM Procedure

Missing Values

Embedded missing values in the dependent variable usually cause no problems in UCM modeling. However, no embedded missing values are allowed in the predictor variables. Certain patterns of missing values in the dependent variable can lead to failure of the initialization step of the diffuse Kalman filtering for some models. For example, if in a monthly series all values are missing for a certain month—say, May—then a BSM with monthly seasonality leads to such a situation. However, in this case the initialization step can complete successfully for a nonseasonal model such as local linear model.