lasso.firstq: Determine the first q Predictors in the Lasso Path
In hdi: High-Dimensional Inference

Description Usage Arguments Details Value Author(s) See Also Examples

Determines the q predictors that enter the lasso path first.

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

`x`	numeric design matrix (without intercept) of dimension n 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`.

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

Vector of selected predictors.

Lukas Meier

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

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