fortify.lm

0th

Percentile

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

If you have missing values in your model data, you may need to refit the model with na.action = na.exclude.

Usage
"fortify"(model, data = model$model, ...)
Arguments
model
linear model
data
data set, defaults to data used to fit model
...
not used by this method
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

Aliases
  • fortify.lm
Examples
mod <- lm(mpg ~ wt, data = mtcars)
head(fortify(mod))
head(fortify(mod, mtcars))

plot(mod, which = 1)

ggplot(mod, aes(.fitted, .resid)) +
  geom_point() +
  geom_hline(yintercept = 0) +
  geom_smooth(se = FALSE)

ggplot(mod, aes(.fitted, .stdresid)) +
  geom_point() +
  geom_hline(yintercept = 0) +
  geom_smooth(se = FALSE)

ggplot(fortify(mod, mtcars), aes(.fitted, .stdresid)) +
  geom_point(aes(colour = factor(cyl)))

ggplot(fortify(mod, mtcars), aes(mpg, .stdresid)) +
  geom_point(aes(colour = factor(cyl)))

plot(mod, which = 2)
ggplot(mod) +
  stat_qq(aes(sample = .stdresid)) +
  geom_abline()

plot(mod, which = 3)
ggplot(mod, aes(.fitted, sqrt(abs(.stdresid)))) +
  geom_point() +
  geom_smooth(se = FALSE)

plot(mod, which = 4)
ggplot(mod, aes(seq_along(.cooksd), .cooksd)) +
  geom_bar(stat = "identity")

plot(mod, which = 5)
ggplot(mod, aes(.hat, .stdresid)) +
  geom_vline(size = 2, colour = "white", xintercept = 0) +
  geom_hline(size = 2, colour = "white", yintercept = 0) +
  geom_point() + geom_smooth(se = FALSE)

ggplot(mod, aes(.hat, .stdresid)) +
  geom_point(aes(size = .cooksd)) +
  geom_smooth(se = FALSE, size = 0.5)

plot(mod, which = 6)
ggplot(mod, aes(.hat, .cooksd)) +
  geom_vline(xintercept = 0, colour = NA) +
  geom_abline(slope = seq(0, 3, by = 0.5), colour = "white") +
  geom_smooth(se = FALSE) +
  geom_point()

ggplot(mod, aes(.hat, .cooksd)) +
  geom_point(aes(size = .cooksd / .hat)) +
  scale_size_area()
Documentation reproduced from package ggplot2, version 2.1.0, License: GPL-2

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