JuliaStats
Add `BernoulliLogit`
This PR adds a Bernoulli distribution with the logit of the success rate as parameter.
This is motivated by use cases e.g. in Turing (https://github.com/TuringLang/Turing.jl/issues/1890) where it is more convenient to work with unconstrained parameters. First class support for the parameterization allows us to evaluate e.g. the log pdf more efficiently.
Can you mention “parametrized by the log of the odds Logitp = p/(1-p)” in the docstring
Codecov Report
Base: 85.94% // Head: 85.50% // Decreases project coverage by -0.44% :warning:
Coverage data is based on head (
9ed9c73) compared to base (4c27f7d). Patch coverage: 12.00% of modified lines in pull request are covered.
Additional details and impacted files
@@ Coverage Diff @@
## master #1623 +/- ##
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- Coverage 85.94% 85.50% -0.45%
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Files 129 130 +1
Lines 8098 8155 +57
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+ Hits 6960 6973 +13
- Misses 1138 1182 +44
| Impacted Files | Coverage Δ | |
|---|---|---|
| src/Distributions.jl | 100.00% <ø> (ø) |
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| src/univariates.jl | 74.07% <ø> (ø) |
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| src/univariate/discrete/bernoullilogit.jl | 12.00% <12.00%> (ø) |
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| src/univariate/continuous/skewnormal.jl | 65.62% <0.00%> (ø) |
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| src/eachvariate.jl | 90.47% <0.00%> (+4.76%) |
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Can you mention “parametrized by the log of the odds
Logitp = p/(1-p)” in the docstring
Are you interested in the term "log-odds" specifically? The docstring already mentions that it is parameterized by the logit of the success rate, and log-odds is just another name for the logit (see e.g. https://en.wikipedia.org/wiki/Logit).
The docstring already mentions that it is parameterized by the logit of the success rate
Well, that requires you knowing what a logit is. Saying it is "parametrised by logitp = log(p/(1-p)) where p is the success rate" makes everything immediately clear to the passerby - doesn't it?
Ah I see, I thought the main point of your comment was the term log odds. I changed the docstring, hopefully it is clearer now.