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
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
Value
Coefficients from the model.
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.