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.

Sign up for GitHub

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

Jump to bottom

Implement logcdf method for discrete distributions #4387

Merged
merged 9 commits into from
Dec 31, 2020
Merged

Implement logcdf method for discrete distributions #4387

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
47021d4
Implement logcdf method for discrete distributions
ricardoV94 Dec 17, 2020
0583d8e
Add release note
ricardoV94 Dec 28, 2020
a09d93b
Small reformatting
ricardoV94 Dec 28, 2020
831afba
Add more comprehensive bound check for impossible parameters
ricardoV94 Dec 28, 2020
450a6f7
Fix bounds for logcdf of DiscreteUniform
ricardoV94 Dec 28, 2020
2c3c2a0
Add safe values/ parameters for `BetaBinomial`, `Poisson`, and `Hyper…
ricardoV94 Dec 29, 2020
670a652
Change `check_selfconsistency_discrete_logcdf` to work with negative …
ricardoV94 Dec 29, 2020
bcf87a2
Raise TypeError in logcdf methods that only accept scalar values.
ricardoV94 Dec 31, 2020
dc4ce4a
Small change to logcdf methods of `DiscreteWeibull` and `ZeroInflated…
ricardoV94 Dec 31, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions RELEASE-NOTES.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ It also brings some dreadfully awaited fixes, so be sure to go through the chang
- Option to set `check_bounds=False` when instantiating `pymc3.Model()`. This turns off bounds checks that ensure that input parameters of distributions are valid. For correctly specified models, this is unneccessary as all parameters get automatically transformed so that all values are valid. Turning this off should lead to faster sampling (see [#4377](https://github.com/pymc-devs/pymc3/pull/4377)).
- `OrderedProbit` distribution added (see [#4232](https://github.com/pymc-devs/pymc3/pull/4232)).
- `plot_posterior_predictive_glm` now works with `arviz.InferenceData` as well (see [#4234](https://github.com/pymc-devs/pymc3/pull/4234))
- Add `logcdf` method to all univariate discrete distributions (see [#4387](https://github.com/pymc-devs/pymc3/pull/4387)).

### Maintenance
- Fixed bug whereby partial traces returns after keyboard interrupt during parallel sampling had fewer draws than would've been available [#4318](https://github.com/pymc-devs/pymc3/pull/4318)
Expand Down
Loading