I am using MLForecast version 0.6.2. It's a managed environment so updating a package is a process that takes time is not entirely in my control. If there is anything about the older version that might explain the below I'd appreciate knowing that too. After doing a

mlf.preprocess

and looking at my transformations, I'm seeing a few things I'm wondering about. They are: • How do I have values for lags that don't exist? For example, a lag of 1 in the same line as the first value not being null. • Same with expanding means and seasonal means. • Maybe this is causing the issue I'm seeing with expanding mean or maybe not. I thought an expanding mean was the mean for all values up to a position of interest. So, in row 3 of a series it'd be the mean of rows 1-3. No? I'm seeing different for the expanding mean that I calculate using the above understanding. Appreciate any help. Thanks