Is there a Julia package that can decompose a time series data into trend, seasonality and random?

I asked a similar question a while ago, and apparently there isn’t any. I have implemented Hamilton (2017) for detrending, and plan to release it soon. I also came up with a simple multilevel model-based deseasonalizer that seems to work surprisingly well, but that is still experimental.

As I said in the other topic, most of these methods introduce spurious patterns, especially for the “trend”. Deseasonalizing with sophisticated algorithms (STL or X13-ARIMA-SEATS) is also prone to this, to a smaller extent. But of course they are OK for exploratory plotting, one just has to be aware of this.