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CovSel

Model-Free Covariate Selection

Model-free selection of covariates under unconfoundedness for situations where the parameter of interest is an average causal effect. This package is based on model-free backward elimination algorithms proposed in de Luna, Waernbaum and Richardson (2011). Marginal co-ordinate hypothesis testing is used in situations where all covariates are continuous while kernel-based smoothing appropriate for mixed data is used otherwise.

Versions across snapshots

VersionRepositoryFileSize
1.2.2 rolling linux/jammy R-4.5 CovSel_1.2.2.tar.gz 337.4 KiB
1.2.2 rolling linux/noble R-4.5 CovSel_1.2.2.tar.gz 337.1 KiB
1.2.2 rolling source/ R- CovSel_1.2.2.tar.gz 168.9 KiB
1.2.2 latest linux/jammy R-4.5 CovSel_1.2.2.tar.gz 337.4 KiB
1.2.2 latest linux/noble R-4.5 CovSel_1.2.2.tar.gz 337.1 KiB
1.2.2 latest source/ R- CovSel_1.2.2.tar.gz 168.9 KiB
1.2.2 2026-04-26 source/ R- CovSel_1.2.2.tar.gz 168.9 KiB
1.2.2 2026-04-23 source/ R- CovSel_1.2.2.tar.gz 168.9 KiB
1.2.2 2026-04-09 windows/windows R-4.5 CovSel_1.2.2.zip 340.2 KiB
1.2.2 2025-04-20 source/ R- CovSel_1.2.2.tar.gz 168.9 KiB

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