kmedved

Understood. I took a look at how the [MERF package handles this](https://github.com/manifoldai/merf/issues/18), but the solution does not seem transferable unfortunately. Thanks for all your work on this package - eager...

Thanks - that's helpful context. FWIW, I would be interested in a similar solution, even if it is not statistically sound. It may still generate useful results in some contexts,...

This would be very helpful if possible to add. It's unfortunately over my head to work on, both in a math and coding sense.

@CDonnerer - just want to say that's a fantastic library you've written. I don't know how practical it would be to port the features over to NGboost as @alejandroschuler suggested,...

Thanks @ryan-wolbeck. This remains something I'm super interested in (any skewed regression distributions would be a huge step), but having taken a shot, the math is over my head for...

@schorrm I'm friendly with Tango on twitter and can ask him for help here if still needed, although it looks like @Maradonna90 may have solved this? Let me know if...

The NBA schedule can be found on the CDN page here: https://cdn.nba.com/static/json/staticData/scheduleLeagueV2.json @rsforbes. Similar to @JaumeClave's link, this site also appears to have the schedule: https://data.nba.com/data/10s/v2015/json/mobile_teams/nba/2020/league/00_full_schedule_week_tbds.json. I'm not sure about...

Try season type `PlayIn`

This would be a huge improvement. I've been holding off with this library until this is ready. Thanks!

I may be misunderstanding this issue (I came here from #154). I was thinking of adding a `sample_weight` parameter, similar to what you see in scikit-learn, xgboost, catboost, lightgbm, etc......