Plot a Recorded Selection

Draws one step of a selection recorded by surreal_path(), as a row of panels: the share each step explained, the criterion along the path, and the residual plot of the model at the step.

Usage

# S3 method for class 'surreal_path'
plot(x, step = x$best, panels = c("explained", "criterion", "residuals"), ...)

Arguments

x

A surreal_path object.

step

Integer. The step to draw, from 0 to the number of predictors. Default is the best step.

panels

Character. The panels to draw, in order, from "explained", "coefficients", "criterion" and "residuals". Default is all but "coefficients". Four panels are drawn two to a row.

...

Further arguments passed to plot() for the residual plot.

Value

x, invisibly. Called for the plot it draws.

Details

The panels are:

• "explained": a bar for each step, on a log scale, for the share of the variation left before the step that its predictor explained. A dotted line marks the criterion's charge for a predictor: the least a step has to explain for the criterion to fall. The bars above it are the steps that improved the model.

• "coefficients": the coefficient of every predictor along the path.

• "criterion": the criterion along the path.

• "residuals": the residual plot of the model at the step.

A solid violet line marks the step that is drawn, and a dashed green line the best step. A predictor is blue once it is in the model at the step, and gray until then. A decoy in the model is orange, when the path knows its decoys.

Examples

set.seed(114)
hidden <- surreal(r_logo_image_data)
path <- surreal_path(surreal_decoys(hidden, n = 20))

plot(path)

plot(path, step = 25)


# The coefficient paths, with the criterion beside them
plot(path, panels = c("coefficients", "criterion"))