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glmmsel - Generalised Linear Mixed Model Selection

Provides tools for fitting sparse generalised linear mixed models with l0 regularisation. Selects fixed and random effects under the hierarchy constraint that fixed effects must precede random effects. Uses coordinate descent and local search algorithms to rapidly deliver near-optimal estimates. Gaussian and binomial response families are currently supported. For more details see Thompson, Wand, and Wang (2025) <doi:10.48550/arXiv.2506.20425>.

Last updated

openblascpp

4.18 score 5 scripts 231 downloads

familial - Statistical Tests of Familial Hypotheses

Provides functionality for testing familial hypotheses. Supports testing centers belonging to the Huber family. Testing is carried out using the Bayesian bootstrap. One- and two-sample tests are supported, as are directional tests. Methods for visualizing output are provided.

Last updated

4.18 score 3 stars 6 scripts 229 downloads

grpsel - Group Subset Selection

Provides tools for sparse regression modelling with grouped predictors using the group subset selection penalty. Uses coordinate descent and local search algorithms to rapidly deliver near optimal estimates. The group subset penalty can be combined with a group lasso or ridge penalty for added shrinkage. Linear and logistic regression are supported, as are overlapping groups.

Last updated

openblascpp

4.00 score 2 stars 6 scripts 258 downloads