coef.SLOPE: Obtain coefficients

In SLOPE: Sorted L1 Penalized Estimation

Obtain coefficients

Description

This function returns coefficients from a model fit by SLOPE().

Usage

## S3 method for class 'SLOPE'
coef(
  object,
  alpha = NULL,
  exact = FALSE,
  simplify = TRUE,
  intercept = TRUE,
  scale = c("original", "normalized"),
  sigma,
  ...
)

Arguments

object	an object of class 'SLOPE'.
alpha	penalty parameter for SLOPE models; if NULL, the values used in the original fit will be used
exact	if TRUE and the given parameter values differ from those in the original fit, the model will be refit by calling stats::update() on the object with the new parameters. If FALSE, the predicted values will be based on interpolated coefficients from the original penalty path.
simplify	if TRUE, base::drop() will be called before returning the coefficients to drop extraneous dimensions
intercept	whether to include the intercept in the output; only applicable when simplify = TRUE and an intercept has been fit.
scale	whether to return the coefficients in the original scale or in the normalized scale.
sigma	deprecated. Please use alpha instead.
...	arguments that are passed on to stats::update() (and therefore also to SLOPE()) if exact = TRUE and the given penalty is not in object

Details

If exact = FALSE and alpha is not in object, then the returned coefficients will be approximated by linear interpolation. If coefficients from another type of penalty sequence (with a different lambda) are required, however, please use SLOPE() to refit the model.

Value

Coefficients from the model.

See Also

predict.SLOPE(), SLOPE()

Other SLOPE-methods: deviance.SLOPE(), plot.SLOPE(), predict.SLOPE(), print.SLOPE(), score()

Examples

fit <- SLOPE(mtcars$mpg, mtcars$vs, path_length = 10)
coef(fit)
coef(fit, scale = "normalized")

SLOPE documentation built on July 2, 2025, 9:07 a.m.