cov.sel.high.lasso: cov.sel.high.lasso
In CovSelHigh: Model-Free Covariate Selection in High Dimensions

Description Usage Arguments Details Value Author(s) See Also

Function called by cov.sel.high if type="lasso". Not meant to be used on its own.

1	cov.sel.high.lasso(Y, X, minscreen = 2, ...)

`Y`	Outcome variable or treatment variable.
`X`	A matrix or data frame containing columns of covariates and all functions of covariates e.g. interactions that should be included in the lasso model.
`minscreen`	The minimum number of columns in X that should be selected.
`...`	Additional arguments passed on to `cv.glmnet`.

See cv.glmnet.

cov.sel.high.lasso returns a logical vector of the same length as the number of columns in X. The positions of values in the vector refers to the (functions of) covariates in the corresponding X columns. Value TRUE implies that (the function of) the covariate has a corresponding coefficient not equal to zero.

Jenny Häggström, <jenny.haggstrom@umu.se>

cv.glmnet

CovSelHigh documentation built on May 2, 2019, 3:25 a.m.