Repository navigation
docs(05): scale-normalize the ACNet generator plot - #8
Merged
Merged
Conversation
Archimedean generators are identified only up to a scaling of their argument (phi(t) and phi(ct) give the same copula), so the raw overlay looked far off even though the fitted copula matched (LL near the Clayton ceiling). Normalize both generators to phi'(0) = -1 before plotting; the learned ACNet now visibly tracks the true Clayton, with a small residual = genuine approximation error. Added a markdown note explaining the identifiability.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
The ACNet notebook's generator overlay looked badly off from Clayton even though the copula was well-recovered (fitted LL ≈ Clayton ceiling). Cause: Archimedean generators are identified only up to a scaling of the argument —$\varphi(t)$ and $\varphi(ct)$ give the same copula, so the likelihood can't fix the scale.
Fix: normalize both generators to$\varphi'(0) = -1$ before plotting. The learned ACNet now clearly tracks the true Clayton, with a small residual = genuine approximation error (finite mixture of exponentials vs Clayton's Gamma-frailty transform). Added a markdown note on the identifiability. Notebook re-executed and committed.