pymc-devs / pymc-devs/pytensor-distributions
Add distributions
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 5
- Forks
- 4
- Avg merge
- 3h 13m
- Merged PRs (30d)
- 9
Description
This is a list to keep track of the currently implemented distributions and the ones still missing.
- asymmetric_laplace
- bernoulli
- betabinomial
- beta
- betascaled
- binomial
- categorical
- cauchy
- chi_squared
- discrete_uniform
- discrete_weibull
- exgaussian
- exponential
- gamma
- geometric
- gumbel
- halfcauchy
- halfnormal
- halfstudentt
- hypergeometric
- inversegamma
- kumaraswamy
- laplace
- logistic
- logitnormal
- loglogistic
- lognormal
- moyal
- negativebinomial
- normal
- pareto
- poisson
- rice
- scaled_inverse_chi_squared
- skewnormal
- skew_studentt
- studentt
- triangular
- truncatednormal
- uniform
- vonmises
- wald
- weibull
- zi_binomial
- zi_negativebinomial
- zi_poisson
- Multivariate Normal
- Dirichlet
Modifiers (for the moment, we are going to let other libraries like pymc/preliz to handle these)
-
censored -
hurdle -
mixture -
truncated
Implemented in PyMC, not PreliZ
- PolyaGamma
- DirichletMultinomial
- Multinomial
- MvStudentT
- MatrixNormal
- Wishart
- LKJCorr
- StickBreakingWeights
- ???
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Use the distribution checklist in the issue as the starting point, focusing on the unchecked entries and the sections distinguishing modifiers from distributions implemented in PyMC but not PreliZ. No source files, tests, or implementation entry points are named, so completion criteria and the relevant code locations need to be established before work begins.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100