Weber, Sam wrote:
Hi,
I was hoping to get some advice on how to derive estimates of slopes from four
parameter logistic models fit with SSfpl.
I fit the model using:
model<-nls(temp~SSfpl(time,a,b,c,d))
summary(model)
I am interested in the values of the lower and upper asymptotes (parameters a
and b), but also in the gradient of the line at the inflection point (c) which
I assume tells me my rate of increase when it is steepest (?).
However, I cannot work out how to derive a slope estimate. I'm guessing it has
something to do with the scaling parameter d but having searched the internet
for hours I have not made any progress, and it is probably quite simple. Any
help would be hugely appreciated!
Sam,
If I understand you correctly, all you want is the derivative
of the fpl wrt the input. You can differentiate the fpl function
or you can use the result provided by predict.nls() in the
"gradient" attribute. The gradient wrt 'c' is the negative
of the slope you want. The maximum slope will occur at time = c.
So this should give you the slope:
ypred <- predict(model,newdata=data.frame(Time=coef(model)[3]))
myslope <- -attr(ypred, "gradient")[,3]
-Peter Ehlers
All the best
Sam
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