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
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