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

Integrating ZIPLN to PLNmodels #116

Merged
merged 37 commits into from
Jan 23, 2024
Merged

Integrating ZIPLN to PLNmodels #116

merged 37 commits into from
Jan 23, 2024

Conversation

jchiquet
Copy link
Member

@jchiquet jchiquet commented Jan 16, 2024

Zero inflation with V-EM by mean field approximation.

What is done

  • Zero inflation with 3 parametrizations
    • "single" : common, global ZI parameter
    • "row": row-wise ZI parameter (vector with n entries)
    • "col": column-wise ZI parameter (vector with p entries)
    • "covar" : covariate dependent ZI component
  • ZI with 4 covariance models
    • "full" : fully parametrized residual covariance
    • "diagonal" : diagonal residual covariance
    • "spherical" : spherical residual covariance
    • "sparse": sparse inverse covariance ($\ell_1$ based penalty)

In progress

  • proper inclusion and testing of covariates in ZI
  • finish first batch of testing
  • double check the documentation
  • Check and add all required R6 and S3 methods for all ZI objects (predict, coef, sigma)

Latter

  • Use close form for estimation W|Y by implementing LambertW function
  • Network-like methods for ZIPLNfit_sparse
  • ZIPLNnetwork, a collection with PLNfamilly collecting a series of ZIPLNfit_sparse object with automatic grid

@jchiquet jchiquet marked this pull request as ready for review January 17, 2024 21:59
…`ZIPLNfit-class`.

- replace variational variance with variational standard deviation
- No change made in code (potential typos highlighted in review)
- Change filename for consistency with similar files (about S3 methods)
- Change prototype of optimizers in ZIPLNfit to remove unused parameters
- ditch intermediate variables `optim_new_*` in the outer loop
- fix bug with S/S2 in `predict()`
@mahendra-mariadassou mahendra-mariadassou merged commit d3cd585 into master Jan 23, 2024
7 checks passed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants