oscar.binplot: Visualize binary indicator matrix optionally coupled with...

In oscar: Optimal Subset Cardinality Regression (OSCAR) Models Using the L0-Pseudonorm

Visualize binary indicator matrix optionally coupled with cross-validation performance for oscar models

Description

This visualization function makes use of the sparsified beta-coefficient matrix form as a function of cardinality. Optionally, user may showcase cross-validation performance alongside at the same cardinality values.

Usage

oscar.binplot(
  fit,
  cv,
  kmax,
  collines = TRUE,
  rowlines = TRUE,
  cex.axis = 0.6,
  heights = c(0.2, 0.8),
  ...
)

Arguments

fit	Fitted oscar S4-class object
cv	Matrix produced by oscar.cv; rows are cv-folds, cols are k-values
kmax	Maximum cardinality 'k'
collines	Should vertical lines be drawn to bottom part
rowlines	Should horizontal lines be drawn to highlight variables
cex.axis	Axis magnification
heights	Paneling proportions as a numeric vector of length 2
...	Additional parameters passed on to hamlet::hmap

Value

This is a plotting function that does not return anything, but instead draws on a new graphics device.

Examples

if(interactive()){
  data(ex)
  fit <- oscar(x=ex_X, y=ex_Y, k=ex_K, w=ex_c, family='cox')
  fit_cv <- oscar.cv(fit, fold = 10, seed = 123)
  oscar.binplot(fit=fit, cv=fit_cv)
}

oscar documentation built on Oct. 2, 2023, 5:08 p.m.