Comments (1)
seanjtaylor
commented on April 25, 2024
We always suggest you try this and see what sorts of problems ensue. Is suspect the model will have trouble learning the yearly period from only 2 months of data, and it will cause some identification problems for the remaining parameters.
Although we almost never advocate this, one way to get around this is to interpolate your missing data before fitting.
Anyway, my advice is to try both: fit the model with no interpolated values and with a (say) linear interpolation and see if it can pick up the seasonality.
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