Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Outlier detection: Support Cook's distance for SEM models #675

Open
rempsyc opened this issue Jan 30, 2024 · 0 comments
Open

Outlier detection: Support Cook's distance for SEM models #675

rempsyc opened this issue Jan 30, 2024 · 0 comments
Labels
Feature idea 🔥 New feature or request

Comments

@rempsyc
Copy link
Member

rempsyc commented Jan 30, 2024

In the outliers paper, we currently have the following sentence:

 When no method is readily available to detect model-based outliers, such as for structural equation modeling (SEM), looking for multivariate outliers may be of relevance.

Mattan commented:

just found the influence.SEM::genCookDist() function the does just this. [...] I think we can add that to the [check_outliers()] function. [...] I think we need Brenton's input here (:

This issue is a reminder to add this method in the future, since we are removing the reference to SEM in the paper.

@rempsyc rempsyc added the Feature idea 🔥 New feature or request label Jan 30, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Feature idea 🔥 New feature or request
Projects
None yet
Development

No branches or pull requests

1 participant