File: fortify.lm.Rd

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r-cran-ggplot2 1.0.0-1
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% Generated by roxygen2 (4.0.1): do not edit by hand
\name{fortify.lm}
\alias{fortify.lm}
\title{Supplement the data fitted to a linear model with model fit statistics.}
\usage{
\method{fortify}{lm}(model, data = model$model, ...)
}
\arguments{
\item{model}{linear model}

\item{data}{data set, defaults to data used to fit model}

\item{...}{not used by this method}
}
\value{
The original data with extra columns:
  \item{.hat}{Diagonal of the hat matrix}
  \item{.sigma}{Estimate of residual standard deviation when
    corresponding observation is dropped from model}
  \item{.cooksd}{Cooks distance, \code{\link{cooks.distance}}}
  \item{.fitted}{Fitted values of model}
  \item{.resid}{Residuals}
  \item{.stdresid}{Standardised residuals}
}
\description{
If you have missing values in your model data, you may need to refit
the model with \code{na.action = na.exclude}.
}
\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(yintercept = 0) +
  geom_smooth(se = FALSE)
qplot(.fitted, .stdresid, data = mod) +
  geom_hline(yintercept = 0) +
  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)) +
  geom_vline(xintercept = 0, 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_size_area()
}