R help - Oct 2010 - Nonlinear Regression Parameter Shared Across Multiple Data Sets

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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"Jared Blashka" <evilamarant7x at gmail.com> wrote in message 
news:AANLkTinFfMuDugqNkUDVr=FMf0wrRTsbjXJExuki_MRH at
mail.gmail.com...
> 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
>
> [[alternative HTML version deleted]]
>
An approach which works for me (code below to illustrate principle, not 
tried...)

1) combine all three "data sets" into one dataframe with a column
(e.g.
dset) indicating data set (1, 2 or 3)

2) express your formula with upper as single valued and LOGEC50 as a vector 
inderxed by dest e.g.
     Y ~ upper/(1+10^(C-LOGEC50[dset]))

3) in the start list, make LOGEC50 a vector e.g. using -8.5 as start for all 
three LOGEC50 values
   start = 
list(start=list(upper=max(std_no_outliers$Y),LOGEC50=c(-8.5, -8.5, -8.5))

Hope that helps,

Keith J

As an addendum to my question, I'm attempting to apply the solution to the
robust non-linear regression function nlrob from the robustbase package, and
it doesn't work in that situation. I'm getting

allRobustFit <- nlrob(Y ~ (upper)/(1+10^(X-LOGEC50[dset])), data=all
,start=list(upper=max(all$Y),LOGEC50=c(-8.5,-8.5,-8.5)))
Error in nls(formula, data = data, start = start, algorithm = algorithm,  :
  parameters without starting value in 'data': LOGEC50

I'm guessing this is because the nlrob function doesn't know what to do
with
a vector for a start value. Am I correct and is there another method of
using nlrob in the same way?

Thanks,
Jared

On Tue, Oct 12, 2010 at 8:58 AM, Jared Blashka
<evilamarant7x@gmail.com>wrote:
> Thanks so much! It works great.
>
> I had thought the way to do it relied on combining the data sets, but I
> couldn't figure out how to alter the formula to work with the
combination.
>
> Jared
>
>
> On Tue, Oct 12, 2010 at 7:07 AM, Keith Jewell
<k.jewell@campden.co.uk>wrote:
>
>>
>> "Jared Blashka" <evilamarant7x@gmail.com> wrote in
message
>> news:AANLkTinFfMuDugqNkUDVr=FMf0wrRTsbjXJExuki_MRH@mail.gmail.com...
>> > 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$Y),LOGEC50=-8.5))
>> >
>> > Previously, all of the regressions were calculated in Prism, but
I'd
>> like
>> > to
>> > be able to automate the calculation process in a script, which is
why
>> I'm
>> > trying to move to R. The issue I'm running into is that
previously, in
>> > Prism, I was able to calculate a shared value for a constraint so
that
>> all
>> > three data sets shared the same value, but have other constraints
>> > calculated
>> > separately. So Prism would figure out what single value for the
>> constraint
>> > in question would work best across all three data sets. For my
formula,
>> > each
>> > data set needs it's own LOGEC50 value, but the upper value
should be the
>> > same across the 3 sets. Is there a way to do this within R, or
with a
>> > package I'm not aware of, or will I need to write my own nls
function to
>> > work with multiple data sets, because I've got no idea where
to start
>> with
>> > that.
>> >
>> > Thanks,
>> > Jared
>> >
>> > [[alternative HTML version deleted]]
>> >
>> An approach which works for me (code below to illustrate principle, not
>> tried...)
>>
>> 1) combine all three "data sets" into one dataframe with a
column (e.g.
>> dset) indicating data set (1, 2 or 3)
>>
>> 2) express your formula with upper as single valued and LOGEC50 as a
>> vector
>> inderxed by dest e.g.
>>     Y ~ upper/(1+10^(C-LOGEC50[dset]))
>>
>> 3) in the start list, make LOGEC50 a vector e.g. using -8.5 as start
for
>> all
>> three LOGEC50 values
>>   start >>
list(start=list(upper=max(std_no_outliers$Y),LOGEC50=c(-8.5, -8.5, -8.5))
>>
>> Hope that helps,
>>
>> Keith J
>>
>> ______________________________________________
>> 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.
>>
>
>
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