Plot the fitted model's regression coefficients along the regularization path.

```
# S3 method for SLOPE
plot(
x,
intercept = FALSE,
x_variable = c("alpha", "deviance_ratio", "step"),
...
)
```

x

an object of class `"SLOPE"`

intercept

whether to plot the intercept

x_variable

what to plot on the x axis. `"alpha"`

plots
the scaling parameter for the sequence, `"deviance_ratio"`

plots
the fraction of deviance explained, and `"step"`

plots step number.

...

parameters that will be used to modify the call to
`lattice::xyplot()`

An object of class `"trellis"`

, which will be plotted on the
current device unless stored in a variable.

`lattice::xyplot()`

, `SLOPE()`

, `plotDiagnostics()`

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

,
`deviance.SLOPE()`

,
`predict.SLOPE()`

,
`print.SLOPE()`

,
`score()`

# NOT RUN { fit <- SLOPE(heart$x, heart$y) plot(fit) # }