Hi:
Here's an example of how one might do this in a specific example using
geom_text().
# Some fake data:
df <- data.frame(x = 1:10, y = 0.5 + (1:10) + rnorm(10))
# Fit a linear model to the data and save the model object:
mod <- lm(y ~ x, data = df)
# Create a list of character strings - the first component
# produces the fitted model, the second produces a
# string to compute R^2, but in plotmath syntax.
rout <- list(paste('Fitted model: ', round(coef(mod)[1], 3), ' + ',
round(coef(mod)[2], 3), ' x', sep = ''),
paste('R^2 == ', round(summary(mod)[['r.squared']], 3),
sep = '') )
# This looks ugly, but I'm using the round() function to make the
# equations look more sane. coef(mod) extracts the model
# coefficients (intercept, then slope), and
# summary(mod)[['r.squared']] extracts R^2.
# See what they look like:
rout
# Notice that the first component of rout is simply a text string
# that can be passed as is, but the second string needs to be
# wrapped inside an expression, which is what parse = TRUE
# in geom_text() does.
# Now construct the plot; given the (x, y) extent of the data, the
# coordinates make sense, but you have to adapt them to
# your data.
ggplot(df, aes(x, y)) +
geom_smooth(method = 'lm') +
geom_text(aes(x = 2, y = 10, label = rout[[1]]), hjust = 0) +
geom_text(aes(x = 2, y = 9.5, label = rout[[2]]), hjust = 0, parse = TRUE )
hjust = 0 makes the text strings flush left, parse = TRUE in the
second call converts the second string in rout into an expression.
This is fine if your plot is a one-off or two-off deal; the code above
gives you a sense of the programming required. OTOH, if you need to do
this a lot, then you're better off with a function that can automate
the process, which Bryan was kind enough to provide.
I might add that there is a dedicated ggplot2 listserv on google:
ggpl...@googlegroups.com, for which questions like these are well
suited.
HTH,
Dennis
On Thu, Nov 10, 2011 at 5:45 AM, Durant, James T. (ATSDR/DTEM/PRMSB)
<h...@cdc.gov> wrote:
> Hello -
>
> So I am trying to use ggplot2 to show a linear regression between two
> variables, but I want to also show the fit of the line on the graph as well.
>
> I am using ggplot2 for other graphics in what I am working on, so even
> though this would be a fairly easy thing to do in Excel, I would prefer to do
> it in R to keep my look and feel, and I think ggplot2 is just cooler.
>
> Here is a sample script of what I am trying to accomplish:
>
> df<-NULL
> df$x<-rnorm(100)
> df$y<-rnorm(100)
> df<-data.frame(df)
>
> ggplot(df, aes(x=x,y=y))+geom_point()+geom_smooth(method=lm)
>
>
> # would like to be able to showr squared and slope/intercept of lm
>
> VR
>
> Jim
>
>
> James T. Durant, MSPH CIH
> Emergency Response Coordinator
> US Agency for Toxic Substances and Disease Registry
> Atlanta, GA 30341
> 770-378-1695
>
>
>
>
>
> [[alternative HTML version deleted]]
>
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>
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