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BranchGLM - Efficient Best Subset Selection for GLMs via Branch and Bound Algorithms
Performs efficient and scalable glm best subset selection using a novel implementation of a branch and bound algorithm. To speed up the model fitting process, a range of optimization methods are implemented in 'RcppArmadillo'. Parallel computation is available using 'OpenMP'.
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generalized-linear-modelsregressionstatisticssubset-selectionvariable-selectionopenblascppopenmp
5.56 score 8 stars 30 scripts 300 downloadsfastbackward - Fast Backward Elimination Based on Information Criterion
Performs backward elimination with similar syntax to the stepAIC() function from the 'MASS' package. A bounding algorithm is used to avoid fitting unnecessary models, making it much faster.
Last updated
regressionstatisticssubset-selection
2.70 score 1 scripts 607 downloads