JuliaStats
add loglogistic distribution
This PR adds log-logistic distribution to the package.
The log-logistic distribution has two parameters: scale and shape. It has been widely used in survival analysis.
The model implementation is in src/univariate/continuous/loglogistic.jl
The test is in test/univariate/continuous/loglogistic.jl
Codecov Report
Attention: 23 lines in your changes are missing coverage. Please review.
| Files | Coverage Δ | |
|---|---|---|
| src/Distributions.jl | 100.00% <ø> (ø) |
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| src/univariates.jl | 75.90% <ø> (ø) |
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| src/univariate/continuous/loglogistic.jl | 43.90% <43.90%> (ø) |
... and 10 files with indirect coverage changes
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This looks like a pretty solid implementation, but I do wonder if we should be adding Log* distributions piecemeal like this, rather than providing a more general interface for transformed variables.
This looks like a pretty solid implementation, but I do wonder if we should be adding Log* distributions piecemeal like this, rather than providing a more general interface for transformed variables.
It sounds like a very interesting idea to provide a general interface for transformed variables. But I feel there might be some difficulties. 1) commonly used parameterization might not be consistent for distribution on R and its log transformation on R+. 2) it might not be straightforward to "translate" moments. For example, Logistic(a, b) always has a mean value of a, but LogLogistic(c,d) doesn't always have a finite mean. 3) It might be redundant for users to recreate a transformation, especially for popular ones as LogNormal, LogLogistic, LogUniform, etc.