Alternative normalization for Normal
ly distributed parameters?
#250
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
@adelinehillier, should we subtract the mean and divide by variance? We're doing the converse now (subtracting variance and dividing by mean). It seems dividing by the mean has undesirable effects, like the variance in unconstrained space diverging as the constrained mean approaches zero. For example, we can't have unconstrained parameters with unit normal distributions using this method. But subtracting mean and dividing by variance is always valid, and implies that the unconstrained prior is unit
Normal(0, 1)
.