Difference between sigma^2 and MSE in `fable`'s `glance()`?

What is the difference between sigma^2 and MSE in the glance() output?

I would've thought that they would be the same, thinking that:

  • MSE = The mean of the squared errors, where errors = the differences between the training data and the values fitted by the model produced from said training data.
  • sigma^2 = The same.

My guess is that it is something along the lines of sigma^2 being under a transformation.

Referred here by Forecasting: Principles and Practice, by Rob J Hyndman and George Athanasopoulos

Well I figured out part of it. For additive error models:

  • MSE = SSE / (N - 1)
  • sigma^2 = SSE / (N - k - 1)

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