yaglm/organization.txt at main · statistical-python/yaglm · GitHub

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config
------
Implemented the base model parameter configuration objects: loss, penalty, penalty flavor, and constraint. Also includes the tuning objects for these model parameters;


infer
-----
Implements statistical inference procedures such as estimating the degrees of freedom.

metrics
-------
Computes metrics used for model selection and diagnostics such as information criteria.

opt
---
Built in optimization library including FISTA, ADMM, and LLA algorithms. Comes with support for GLM loss functions, penalties and constraints.

cvxpy
-----
Support for cvxpy based solvers.

pen_max
-------
Computes the largest reasonable penalty value for combinations of loss + penalties.

solver
------
Provides the solver wrapper objects that are used to compute the penalized GLM solutions.

tests
-----
Test cases for yaglm.

tune
----
Handles tuning logistics e.g. cross-validation. Also has some tuning diagnostics.