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.

AuthorJenny Häggström, Emma Persson,
Date of publication2015-11-09 17:23:10
MaintainerJenny Häggström <jenny.haggstrom@umu.se>
LicenseGPL-3
Version1.2.1

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Files

CovSel
CovSel/inst
CovSel/inst/CITATION
CovSel/NAMESPACE
CovSel/data
CovSel/data/datc.rda
CovSel/data/lalonde.rda
CovSel/data/datf.rda
CovSel/data/datfc.rda
CovSel/R
CovSel/R/summary.cov.sel.R CovSel/R/cov.sel.R CovSel/R/cov.sel.np.R
CovSel/MD5
CovSel/DESCRIPTION
CovSel/man
CovSel/man/lalonde.Rd CovSel/man/cov.sel.Rd CovSel/man/datc.Rd CovSel/man/datfc.Rd CovSel/man/datf.Rd CovSel/man/summary.cov.sel.Rd CovSel/man/cov.sel.np.Rd

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