-
Notifications
You must be signed in to change notification settings - Fork 10
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
Wiliamson transform sampling v2 #51
Conversation
Codecov Report
@@ Coverage Diff @@
## main #51 +/- ##
==========================================
+ Coverage 77.26% 79.80% +2.54%
==========================================
Files 22 25 +3
Lines 365 421 +56
==========================================
+ Hits 282 336 +54
- Misses 83 85 +2
... and 2 files with indirect coverage changes 📣 Codecov offers a browser extension for seamless coverage viewing on GitHub. Try it in Chrome or Firefox today! |
Waiting on JuliaRegistries/General#94910 to be merged |
@Santymax98 I think I have a propper implementation now using the williamson transform by default as we discuss by mail. I will merge that tomorow (it is midnight in europe right now, i'm going to bed), if you want to take a look at it before ? Then starting tomorow once it is merged and published in the general registry we can start working on it to include your other archimedean models in the package :) |
Fot the moment this implementation is barebone...
We also need documentation and bindings for a few known generators. and a lot of tests.
but otherwise this should work correctly.
In the future, some copulas may leverage this implmentation, in partiuclar the version that provide both the radial dist and the generator (if both are known, better give both).
We would also need the inverswe generator for some functions... maybe it can be provided through another field in the struct ? And/or computed automaticallly..
Exemples from Mcneil+Neshleova where the generator AND the williamson distribution are known analytically could be implemented as exemples