bcat_plt_diag: Regression diagnostic dashboard

In Rbearcat: University of Cincinnati Themes and Utilities for Econometrics and Data Science

Regression diagnostic dashboard

Description

Produce a multi-panel diagnostic plot for a fitted model with UC styling. Optionally prints assumption test results (Breusch-Pagan, Shapiro-Wilk, Durbin-Watson) to the console.

Usage

bcat_plt_diag(
  model,
  which = c(1, 2, 3, 4),
  labels = TRUE,
  n_labels = 3,
  tests = TRUE,
  nrow = NULL,
  ncol = NULL
)

Arguments

model	A fitted model object (e.g., lm, glm).
which	Integer vector specifying which panels to include: 1 = Residuals vs Fitted, 2 = Q-Q Plot, 3 = Scale-Location, 4 = Residuals vs Leverage. Default: c(1, 2, 3, 4).
labels	Logical. Label influential observations? Default is TRUE.
n_labels	Integer. Number of extreme observations to label. Default is 3.
tests	Logical. Print assumption test results to console? Default is TRUE.
nrow	Number of panel rows.
ncol	Number of panel columns.

Value

A patchwork object combining the diagnostic panels.

Author(s)

Saannidhya Rawat

See Also

Other plots: bcat_plt_area(), bcat_plt_bar(), bcat_plt_box(), bcat_plt_coef(), bcat_plt_hist(), bcat_plt_line(), bcat_plt_point(), bcat_plt_ts()

Examples

m <- lm(mpg ~ wt + hp + cyl, data = mtcars)
bcat_plt_diag(m)
bcat_plt_diag(m, which = c(1, 2))

Rbearcat documentation built on March 21, 2026, 5:07 p.m.