Plot CRT/HierNet Results

Plot CRT/HierNet Results

Usage

# S3 method for class 'cjdiag_crt'
plot(
  x,
  type = "robustness",
  top_n = 25L,
  base_size = NULL,
  colors = NULL,
  palette = NULL,
  theme = NULL,
  label_wrap = NULL,
  attribute.names = NULL,
  level.names = NULL,
  ...
)

Arguments

x

A cjdiag_crt object from cj_fit()

type

Plot type: "robustness" (default), "survival", "rank", "mda", or "cv". "rank" is a connected-dot plot of each level's survival statistic (max \(\lambda\) at which the coefficient is nonzero), ordered from most to least attended.

top_n

Number of levels to display. Default 25 for "robustness", "mda", "rank", and "survival". Pass NULL to show every level.

base_size

Font size (default from global options or 12)

colors

Named character vector overriding specific palette colors

palette

Palette name: "default", "colorblind", or "grey"

theme

A complete ggplot2::theme() object (overrides all theme defaults)

label_wrap

Character width for label wrapping (default 35)

attribute.names

Named character vector renaming attributes in display

level.names

Named list for renaming levels

...

Additional arguments passed to primary ggplot2 geom

Value

A ggplot object

See also

Other plotting: plot.cjdiag_forest(), plot.cjdiag_importance(), plot.cjdiag_nmm(), plot.cjdiag_tree()

Examples

# \donttest{
# CRT requires the hierNet package
if (requireNamespace("hierNet", quietly = TRUE)) {
  df <- data.frame(
    y = sample(0:1, 200, TRUE),
    a = factor(sample(c("x","y"), 200, TRUE)),
    b = factor(sample(c("p","q","r"), 200, TRUE))
  )
  crt <- cj_fit(y ~ a + b, data = df, method = "crt",
                 lambda_grid = c(5, 10), n_folds = 2, n_perm = 2)
  plot(crt, type = "robustness")
}

# }