lasso.firstq: Determine the first q Predictors in the Lasso Path

In hdi: High-Dimensional Inference

Determine the first q Predictors in the Lasso Path

Description

Determines the q predictors that enter the lasso path first.

Usage

lasso.firstq(x, y, q, ...)

Arguments

x	numeric design matrix (without intercept) of dimension n \times p.
y	response vector of length n.
q	number of predictors that should be selected, a positive integer.
...	optional additional arguments to be passed to glmnet.

Details

The lasso.firstq function calls glmnet in a special way and simply postprocesses its nonzero predictor list, see its source code.

Value

Vector of selected predictors.

Author(s)

Lukas Meier

See Also

hdi; the default choice for hdi(), lasso.cv. glmnet

Examples

x <- matrix(rnorm(100 * 1000), nrow = 100, ncol = 1000)
y <- x[,1] * 2 + x[,2] * 2.5 + rnorm(100)
sel <- lasso.firstq(x, y, q = 5)
sel # 5 integers from {1,2, ..., 1000},  including '1' and '2', typically

hdi documentation built on April 18, 2025, 3:01 a.m.