gg_resX: Generate residual plot of residuals against predictors

In lindia: Automated Linear Regression Diagnostic

Generate residual plot of residuals against predictors

Description

Generate residual plot of residuals against predictors

Usage

gg_resX(
  fitted.lm,
  plot.all = TRUE,
  scale.factor = 0.5,
  max.per.page = NA,
  ncol = NA
)

Arguments

fitted.lm	a fitted linear model (i.e. lm, glm) that contains fitted regression
plot.all	boolean value to determine whether plot will be return as a plot arranged using 'grid.arrange()'. When set to false, the function would return a list of residual plots. Parameter defaults to TRUE.
scale.factor	numeric; scales the point size and linewidth to allow customized viewing. Defaults to 0.5.
max.per.page	numeric; maximum number of plots allowed in one page. Parameter defaults to fit all plots on one page.
ncol	specify number of columns in resulting plot per page. Default to make a square matrix of the output.

Value

An arranged grid of residuals against predictor values plots in ggplot. If plotall is set to FALSE, a list of ggplot objects will be returned instead. Name of the plots are set to respective variable names.

Examples

library(MASS)
data(Cars93)
# a regression with categorical variable
cars_lm <- lm(Price ~ Passengers + Length + RPM + Origin, data = Cars93)
gg_resX(cars_lm)
# customize which diagnostic plot is included by have gg_resX to return a list of plots
plots <- gg_resX(cars_lm, plot.all = FALSE)
names(plots)     # get name of the plots
exclude_plots <- plots[-1 ]    #exclude certain residual plots
include_plots <- plots[1]      # include certain residual plots
plot_all(exclude_plots)       # make use of plot_all() in lindia
plot_all(include_plots)

lindia documentation built on Aug. 11, 2023, 1:09 a.m.