Excessive division by df in `generate.TSLM()` to obtain the variance of innovations?
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Description
In generate.TSLM(), the variance of generated (non-bootstrapped) innovations is obtained as x$sigma2 / x$df.residual:
https://github.com/tidyverts/fable/blob/a9404d8bdbd2990a49fffcc43257f8a6e9f9a5d3/R/lm.R#L331
Correct me if I'm wrong, but I believe that plain x$sigma2 is in fact the variance we would like to use (sigma2 is obtained as rss/df, I don't see the point of further division by df).
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Research direction
Start in R/lm.R at generate.TSLM() around line 331, and inspect how x$sigma2 and x$df.residual are defined and used for non-bootstrapped innovations. Confirm which variance is intended, then update the behavior if needed and verify that generated innovation variance matches the issue's expectation.
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Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 45/100