ggplot2 (version 4.0.1)

fortify.lm: Supplement the data fitted to a linear model with model fit statistics.

Description

This method is deprecated because using broom::augment() is a better solution to supplement data from a linear model. If you have missing values in your model data, you may need to refit the model with na.action = na.exclude.

Usage

# S3 method for lm
fortify(model, data = model$model, ...)

Value

The original data with extra columns:

.hat

Diagonal of the hat matrix

.sigma

Estimate of residual standard deviation when corresponding observation is dropped from model

.cooksd

Cooks distance, cooks.distance()

.fitted

Fitted values of model

.resid

Residuals

.stdresid

Standardised residuals

Arguments

model

linear model

data

data set, defaults to data used to fit model

...

not used by this method

Examples

mod <- lm(mpg ~ wt, data = mtcars)

# Show augmented model
head(augment(mod))
head(fortify(mod))

# Using augment to convert model to ready-to-plot data
ggplot(augment(mod), aes(.fitted, .resid)) +
  geom_point() +
  geom_hline(yintercept = 0) +
  geom_smooth(se = FALSE)

# Colouring by original data not included in the model
ggplot(augment(mod, mtcars), aes(.fitted, .std.resid, colour = factor(cyl))) +
  geom_point()