Here's my code:
qplot(data=sites, x, y, main="Site 349")
(p <- qplot(data = sites, x, y, xlab = "", ylab = ""))
(p1 <- p + geom_smooth(method = "loess",span=0.5, size = 1.5))
p1 + theme_bw() + opts(title = "Site 349")
Some of the LOESS lines and confidence intervals go below zero, but I would like to restrict the graphics to 0 and positive numbers (because negative do not make sense). How can I do this?
I can't test it without some example data, but
qplot(data=sites, x, y, main="Site 349")
(p <- qplot(data = sites, x, y, xlab = "", ylab = ""))
(p1 <- p + geom_smooth(method = "loess",span=0.5, size = 1.5))
p1 + theme_bw() + opts(title = "Site 349") + ylim(0, foo)
(where foo is a suitable upper limit for your plot) might do the trick. Unlike in base graphics, the xlim() and ylim() commands in ggplot actually restrict the data that are used in making the plot, rather than just the plot window. It might also restrict the geom_smooth() (though I'm not certain).
Edit: After reading a bit more, you might also want to consider switching out the model that geom_smooth is using. Again, not being able to see your data is a problem. But, for example, if it's binary - you can add stat_smooth(method="glm", family="binomial") to get a logit-smoothed line. See ?stat_smooth
for more.
I am seconding Matt Parker's suggestion that you have to change the fitting procedure. One option that often works for positive-only data, is to do the fit on log-scale, and then exponentiate to get results on the original scale. This will guarantee positive only values.
Generating random data that has some of this issues:
d <- data.frame(x=0:100)
d$y <- exp(rnorm(nrow(d), mean=-d$x/40, sd=0.8))
qplot(x,y,data=d) + stat_smooth()
Now we can use ggplot's transformation capabilites to log-transform the y-values, but display the results on an exponential scale (which corresponds to the original one):
qplot(x,y,data=d) + stat_smooth() + scale_y_log10()+coord_trans(ytrans="pow10")
You can see examples like this on the coord_trans help page. If you don't like the y-axis, you can manipulate the breaks and labels.