Abstract
Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood, or as random variables and predicted by the expectation of the unknown values given the data. The difference between these two procedures is illustrated by an example. It is argued that the second procedure is, in general, more relevant for estimating missing values in time series.
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