plot.cv.missoNet {missoNet}

Plot the cross-validation errors produced by cv.missoNet

Description

S3 method for plotting the cross-validation error surface from a fitted 'cv.missoNet' object.

Usage

## S3 method for class 'cv.missoNet'
plot(
  x,
  type = c("cv.heatmap", "cv.scatter"),
  detailed.axes = TRUE,
  plt.surf = TRUE,
  ...
)

Arguments

x

A fitted 'cv.missoNet' object.

type

A character string for the type of plot, can be either "cv.heatmap" (default) or "cv.scatter".

detailed.axes

Logical: whether the detailed axes should be plotted. The default is 'TRUE'.

plt.surf

Logical: whether to draw the error surface. The default is 'TRUE'. This is only needed when 'type' = "cv.scatter".

...

Other graphical arguments used by ‘ComplexHeatmap::Heatmap’ ('type' = "cv.heatmap") or ‘scatterplot3d::scatterplot3d’ ('type' = "cv.scatter").

Value

The plot object.

Author(s)

Yixiao Zeng [e-mail], Celia M.T. Greenwood and Archer Yi Yang.

Examples

## Simulate a dataset.
set.seed(123)  # reproducibility
sim.dat <- generateData(n = 200, p = 10, q = 10, rho = 0.1, missing.type = "MCAR")


## Perform a five-fold cross-validation on the simulated dataset.
cvfit <- cv.missoNet(X = sim.dat$X, Y = sim.dat$Z, kfold = 5,
                     fit.1se = TRUE, permute = TRUE, with.seed = 486)


## Plot the (standardized) mean cross-validated errors in a heatmap.
plot(cvfit, type = "cv.heatmap")

## Plot the (standardized) mean cross-validated errors in a 3D scatterplot.
plot(cvfit, type = "cv.scatter", plt.surf = TRUE)