lines and points in xyplot()
Hi:
Try this:
library('lattice')
xyplot(y ~ x,
type = c('g', 'p'),
panel = function(x, y, ...){
panel.xyplot(x, y, ...)
panel.lines(x, predict(fm), col = 'black', lwd = 2)
}
)
HTH,
Dennis
On Wed, Nov 23, 2011 at 9:18 AM, Doran, Harold <HDoran at air.org> wrote:
Given the following data, I want a scatterplot with the data points and the predictions from the regression.
Sigma <- matrix(c(1,.6,1,.6), 2)
mu <- c(0,0)
dat <- mvrnorm(5000, mu, Sigma)
x <- dat[,1] * 50 + 200
y <- dat[,2] * 50 + 200
fm <- lm(y ~ x)
### This gives the regression line, but not the data
xyplot(y ~ x,
? ? ? ? ? ? ? type = c('g', 'p'),
? ? ? ? ? ? ? panel = function(x, y){
? ? ? ? ? ? ? panel.lines(x, predict(fm))
? ? ? ? ? ? ? }
)
### This gives both data but as point
xyplot(y + predict(fm) ~ x,
? ? ? ? ? ? ? type = c('g', 'p'),
? ? ? ? ? ? ? )
I know I can add an abline easily, but my problem is a bit more complex and the code above is just an example. What is the best way for the predicted data to form a solid line and let the data points remain as points
Harold
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