coef.cv.sparsegl: Extract coefficients from a 'cv.sparsegl' object.

In hierNest: Penalized Regression with Hierarchical Nested Parameterization Structure

Extract coefficients from a 'cv.sparsegl' object.

Description

This function etracts coefficients from a cross-validated [sparsegl()] model, using the stored '"sparsegl.fit"' object, and the optimal value chosen for 'lambda'.

Usage

## S3 method for class 'cv.sparsegl'
coef(object, s = c("lambda.1se", "lambda.min"), ...)

Arguments

object	Fitted [cv.sparsegl()] object.
s	Value(s) of the penalty parameter 'lambda' at which coefficients are desired. Default is the single value 's = "lambda.1se"' stored in the CV object (corresponding to the largest value of 'lambda' such that CV error estimate is within 1 standard error of the minimum). Alternatively 's = "lambda.min"' can be used (corresponding to the minimum of cross validation error estimate). If 's' is numeric, it is taken as the value(s) of 'lambda' to be used.
...	Not used.

Value

The coefficients at the requested value(s) for 'lambda'.

See Also

[cv.sparsegl()] and [predict.cv.sparsegl()].

hierNest documentation built on March 24, 2026, 5:07 p.m.