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

.

```
# S3 method for SLOPE
coef(object, alpha = NULL, exact = FALSE, simplify = TRUE, sigma, ...)
```

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

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`

Coefficients from the model.

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.

Other SLOPE-methods:
`deviance.SLOPE()`

,
`plot.SLOPE()`

,
`predict.SLOPE()`

,
`print.SLOPE()`

,
`score()`

# NOT RUN { fit <- SLOPE(mtcars$mpg, mtcars$vs, path_length = 1) coef(fit) # }