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

In hadley/fortify: Fortify models (and other objects) to convert them into data frames that be more easily visualised.

Description

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

Usage

fortify.lm(model, data=model$model, ...)

Arguments

model	linear model
data	data set, defaults to data used to fit model
...	not used by this method

Details

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

The following statistics will be added to the data frame:

Value

The original data with extra columns:

Examples

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

plot(mod, which = 1)
qplot(.fitted, .resid, data = mod) + geom_hline() + geom_smooth(se = FALSE)
qplot(.fitted, .stdresid, data = mod) + geom_hline() + 
geom_smooth(se = FALSE)
qplot(.fitted, .stdresid, data = fortify(mod, mtcars), 
colour = factor(cyl))
qplot(mpg, .stdresid, data = fortify(mod, mtcars), colour = factor(cyl))

plot(mod, which = 2)
# qplot(sample =.stdresid, data = mod, stat = "qq") + geom_abline()

plot(mod, which = 3)
qplot(.fitted, sqrt(abs(.stdresid)), data = mod) + geom_smooth(se = FALSE)

plot(mod, which = 4)
qplot(seq_along(.cooksd), .cooksd, data = mod, geom = "bar",
stat="identity")

plot(mod, which = 5)
qplot(.hat, .stdresid, data = mod) + geom_smooth(se = FALSE)
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)

qplot(.hat, .stdresid, data = mod, size = .cooksd) + 
geom_smooth(se = FALSE, size = 0.5)

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

hadley/fortify documentation built on May 17, 2019, 10:15 a.m.