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

changed ar1 logp to use ar1 precision instead of innovation precision #3899

Merged
merged 13 commits into from
Jun 11, 2020
1 change: 1 addition & 0 deletions RELEASE-NOTES.md
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
- `pm.LKJCholeskyCov` now automatically computes and returns the unpacked Cholesky decomposition, the correlations and the standard deviations of the covariance matrix (see [#3881](https://github.com/pymc-devs/pymc3/pull/3881)).

### Maintenance
- AR1 model correctly calculates likelihood of the first observation of a sample, see [#3899](https://github.com/pymc-devs/pymc3/pull/3899)
AlexAndorra marked this conversation as resolved.
Show resolved Hide resolved
- Tuning results no longer leak into sequentially sampled `Metropolis` chains (see #3733 and #3796).
- In named models, `pm.Data` objects now get model-relative names (see [#3843](https://github.com/pymc-devs/pymc3/pull/3843)).
- `pm.sample` now takes 1000 draws and 1000 tuning samples by default, instead of 500 previously (see [#3855](https://github.com/pymc-devs/pymc3/pull/3855)).
Expand Down
Loading