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It would be nice to start implementing models which have analytical evidence formulas, both to show in examples in the docs, and to use as unit tests. I think we can create a new submodule, Models, and write a bunch of log-likelihood functions and priors, using const GMM = NestedModel(log_GMM, prior_GMM). Ideally these models can be written without any additional dependencies than are already present.
For inspiration, here are some papers/repos which have models defined, usually in python
It would be nice to start implementing models which have analytical evidence formulas, both to show in examples in the docs, and to use as unit tests. I think we can create a new submodule,
Models
, and write a bunch of log-likelihood functions and priors, usingconst GMM = NestedModel(log_GMM, prior_GMM)
. Ideally these models can be written without any additional dependencies than are already present.For inspiration, here are some papers/repos which have models defined, usually in python
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