See also the scripts in http://biostat.mc.vanderbilt.edu/BioMod
Frank William Dunlap wrote > > It is more direct to use predict() instead of reconstructing > by hand the prediction expression from the formula given > to lm(). E.g., > > > x <- seq(1,6,by=1/4) > > y <- sin(x) + rnorm(length(x), 0, 1/4) > > plot(x, y) > > fits <- lapply(1:3, function(degree)lm(y~poly(x, deg=degree))) > > xpred <- pretty(x, n=50) > > predictions <- lapply(fits, predict, newdata=list(x=xpred)) > > invisible(lapply(seq_along(fits), function(i)lines(xpred, > predictions[[i]], col=i))) > > If you change your fitting function, say to rq, or your formula, say to > use a > categorical variable or interaction, you don't have to change anything > else, > as the predict method for a model type takes care of the details. > > Bill Dunlap > Spotfire, TIBCO Software > wdunlap tibco.com > > >> -----Original Message----- >> From: r-help-bounces@ [mailto:r-help-bounces@] On Behalf >> Of Robert Baer >> Sent: Wednesday, June 13, 2012 8:40 AM >> To: Kristi Glover; R-help >> Subject: Re: [R] How to plot linear, cubic and quadratic fitting curve in >> a figure? >> >> >> > dput(test) >> structure(list(sp = c(4L, 5L, 9L, 12L, 14L), env = c(12L, 18L, >> 20L, 17L, 15L)), .Names = c("sp", "env"), class = "data.frame", row.names >> = >> c(NA, >> -5L)) >> > plot(test$sp~test$env, main = "S vs. temp", xlim=c(0,20), ylim=c(0,14), >> > ylab="S",xlab="env") >> > linear<-lm(test$sp~test$env) >> > quadratic<-lm(test$sp~test$env+I(test$env^2)) >> > #summary(quadratic) >> > cubic<-lm(test$sp~test$env+I(test$env^2)+I(test$env^3)) >> > #summary(cubic) >> > #fitting curve >> > abline(linear) >> > >> Thanks and waiting for your suggestions >> >> sincerely, >> Kristi Glover >> >> Try adding the following lines of code >> cq = coef(quadratic) >> cc = coef(cubic) >> newenv = seq(min(test$env), max(test$env), by = (max(test$env) - >> min(test$env))/500) >> sp.quad = cq[1] + cq[2]*newenv +cq[3]*newenv^2 >> lines(newenv,sp.quad, col='red') >> >> sp.cubic = cc[1] + cc[2]*newenv +cc[3]*newenv^2 +cc[4]*newenv^3 >> lines(newenv, sp.cubic, col='blue', lty=2) >> >> ------------------------------------------ >> Robert W. Baer, Ph.D. >> Professor of Physiology >> Kirksville College of Osteopathic Medicine >> A. T. Still University of Health Sciences >> 800 W. Jefferson St. >> Kirksville, MO 63501 >> 660-626-2322 >> FAX 660-626-2965 >> >> ______________________________________________ >> R-help@ 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. > > ______________________________________________ > R-help@ 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. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/How-to-plot-linear-cubic-and-quadratic-fitting-curve-in-a-figure-tp4633268p4633297.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.
