The selection project
This project contains software for selective inference, with emphasis on selective inference in regression.
Some key references
A significance test for the lasso: http://arxiv.org/abs/1301.7161
Tests in adaptive regression via the Kac-Rice formula: http://arxiv.org/abs/1308.3020
Post-selection adaptive inference for Least Angle Regression and the Lasso: http://arxiv.org/abs/1401.3889
Exact post-selection inference with the lasso: http://arxiv.org/abs/1311.6238
Exact Post Model Selection Inference for Marginal Screening: http://arxiv.org/abs/1402.5596
Install
git submodule init # travis_tools and C-software
git submodule update
pip install -r requirements.txt
python setup.py install
Potential speedups
We can condition on “parts” of each draw of the sampler, in particular if we condition on the projection of the rejection sample - center onto direction then resampling on the ray can be sped up for some things like LASSO. Could be some cost in power.
Learning a higher dimensional function can perhaps save some time – proper conditioning has to be checked.
Metadata
Release files for selectinf 0.1.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| selectinf-0.1.3.tar.gz | 18.4 MB | Without provenance | Details for selectinf-0.1.3.tar.gz |
Built distributions (wheels)
Total release size: 26.7 MB
Release files / selectinf-0.1.3.tar.gz
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Release files / selectinf-0.1.3-cp37-cp37m-manylinux1_i686.whl
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