SplitKnockoff
2.1Split Knockoffs for Structural Sparsity
Overview
Split Knockoff is a data adaptive variable selection framework for controlling the (directional) false discovery rate (FDR) in structural sparsity, where variable selection on linear transformation of parameters is of concern. This proposed scheme relaxes the linear subspace constraint to its neighborhood, often known as variable splitting in optimization. Simulation experiments can be reproduced following the Vignette. 'Split Knockoffs' is first defined in Cao et al. (2021) doi:10.48550/arXiv.2103.16159.
Install
Health
- NOTE r-devel-linux-x86_64-fedora-clang
- NOTE r-devel-linux-x86_64-fedora-gcc
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
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Code & Tests
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Package metadata
- First published
- 2021-09-13
- Total releases
- 5 / 5 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 31 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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