I'm working with 3 different data sets and applying this non-linear
regression formula to each of them.
nls(Y ~ (upper)/(1+10^(X-LOGEC50)), data=std_no_outliers,
start=list(upper=max(std_no_outliers$Y),LOGEC50=-8.5))
Previously, all of the regressions were calculated in Prism, but I'd like to
be able to automate the calculation process in a script, which is why I'm
trying to move to R. The issue I'm running into is that previously, in
Prism, I was able to calculate a shared value for a constraint so that all
three data sets shared the same value, but have other constraints calculated
separately. So Prism would figure out what single value for the constraint
in question would work best across all three data sets. For my formula, each
data set needs it's own LOGEC50 value, but the upper value should be the
same across the 3 sets. Is there a way to do this within R, or with a
package I'm not aware of, or will I need to write my own nls function to
work with multiple data sets, because I've got no idea where to start with
that.
Thanks,
Jared
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