Hi!
I have fitted two glms assuming a poisson distribution which are:
fit1 <- glm(Aids ~ Year, data=aids, family=poisson())
fit2 <- glm(Aids ~ Year+I(Year^2), data=aids, family=poisson())
I am trying to work out how to represent the fitted regression curves of fit1
and fit2 on the one graph. I have tried:
graphics.off()
plot(Aids ~ Year, data = aids)
line(glm(Aids ~ Year, data=aids, family=poisson()))
line(glm(Aids ~ Year+I(Year^2), data=aids, family=poisson()))
but this does not work.
Can anyone help me?
Thanks
Jo
BSES Limited Disclaimer
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One approach to this is generating a representative sequence of your x-variable(s) with seq() or expand.grid(). Next use the predict() function to make predictions from your glm object along the sequence. Finally, plot the predictions vs. the new sequence. Putting everything into a dataframe helps. # generate some data: x <- rnorm(10) y <- x * 2 + rnorm(10, sd=0.5) # plot plot(y ~ x) # generate linear model: l <- lm(y ~ x) # generate sequence along x-var # and predictions d <- data.frame(x.new=seq(from=-1.5, to=1.2, by=0.1)) d$y.new <- predict(l, data.frame(x=d$x.new)) # add to plot: lines(y.new ~ x.new, data=d, lwd=2) Cheers, Dylan On Sun, Jun 7, 2009 at 8:36 PM, Jo Stringer<JStringer at bses.org.au> wrote:> Hi! > > > I have fitted two glms assuming a poisson distribution which are: > > fit1 <- glm(Aids ~ Year, data=aids, family=poisson()) > > fit2 <- glm(Aids ~ Year+I(Year^2), data=aids, family=poisson()) > > > I am trying to work out how to represent the fitted regression curves of fit1 and fit2 on the one graph. I have tried: > > graphics.off() > > plot(Aids ~ Year, data = aids) > > > line(glm(Aids ~ Year, data=aids, family=poisson())) > line(glm(Aids ~ Year+I(Year^2), data=aids, family=poisson())) > > but this does not work. > > Can anyone help me? > > Thanks > > Jo > > BSES Limited Disclaimer > > -------------------------------------------------------------------------------- > > This email and any files transmitted with it are confide...{{dropped:15}} > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
Hi Jo, Next time try prepare a reproducible code. You have several ways of do that (see Dylan Beaudette) and give a look below. x<-1:100 y<-7+x*(sqrt(x*runif(100))) plot(y~x) mod1<-glm(y~x) mod2<-glm(y~x+I(x*x)) curve(mod1$coef[1]+mod1$coef[2]*x, col="red", add=T, lwd=3) curve(mod2$coef[1]+mod2$coef[2]*x+mod2$coef[3]*x*x, col="green", add=T, lwd=3) cheers milton On Sun, Jun 7, 2009 at 11:36 PM, Jo Stringer <JStringer@bses.org.au> wrote:> Hi! > > > I have fitted two glms assuming a poisson distribution which are: > > fit1 <- glm(Aids ~ Year, data=aids, family=poisson()) > > fit2 <- glm(Aids ~ Year+I(Year^2), data=aids, family=poisson()) > > > I am trying to work out how to represent the fitted regression curves of > fit1 and fit2 on the one graph. I have tried: > > graphics.off() > > plot(Aids ~ Year, data = aids) > > > line(glm(Aids ~ Year, data=aids, family=poisson())) > line(glm(Aids ~ Year+I(Year^2), data=aids, family=poisson())) > > but this does not work. > > Can anyone help me? > > Thanks > > Jo > > BSES Limited Disclaimer > > > -------------------------------------------------------------------------------- > > This email and any files transmitted with it are confide...{{dropped:15}} > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Since you have provided no executable data and not even a clear enough description of the data to offer advice regarding approaches or pitfalls, I will use the example in glm's help page: counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) glm.D93r <- glm(counts ~ outcome, family=poisson()) plot(x=as.numeric(as.character(outcome)), y=counts, type="p") #need to convert from factor to ge points lines(1:3, c(exp(3.045), exp(3.0445 -0.4543), exp(3.0445 -0.2930) ) ) #the default link for poisson is log, so you need to transform back to the original scale to predict counts. On Jun 7, 2009, at 11:36 PM, Jo Stringer wrote:> > I have fitted two glms assuming a poisson distribution which are: > > fit1 <- glm(Aids ~ Year, data=aids, family=poisson()) > > fit2 <- glm(Aids ~ Year+I(Year^2), data=aids, family=poisson()) > > > I am trying to work out how to represent the fitted regression > curves of fit1 and fit2 on the one graph. I have tried: > > graphics.off() > > plot(Aids ~ Year, data = aids) > > > line(glm(Aids ~ Year, data=aids, family=poisson())) > line(glm(Aids ~ Year+I(Year^2), data=aids, family=poisson())) > > but this does not work. > > Can anyone help me?David Winsemius, MD Heritage Laboratories West Hartford, CT