nls not converging for zero-noise cases
Setzer.Woodrow at epamail.epa.gov writes:
No doubt Doug Bates would gladly accept patches ... .
The zero-noise case is irrlevant in practice, but quite often I have uttered
/(!! (vituperation filter on) when nls did not converge with real data. The
Yours truly dieter.menne at menne-biomed.de writes:
...
Recently, a colleague fitted gastric emptying
curves using GraphPad, with 100% success, and
nls failed for one third of these. When we
checked GraphPads output more closely, some of
the coefficients looked like 2.1 with a confidence
Earl F. Glynn efg at stowers-institute.org writes:
It's not clear to me why this problem cannot be fixed somehow. You
You might try optim instead of nls, which always (well, as far I used it)
converges. However, resulting coefficients may be totally off, and you should
use profiling to check
Earl F. Glynn wrote:
Berton Gunter [EMAIL PROTECTED] wrote in message
news:[EMAIL PROTECTED]
Or, maybe there's something I don't understand about the
algorithm being used.
Indeed! So before making such comments, why don't you try to learn about
it?
Doug Bates is a pretty smart guy, and
Joerg van den Hoff [EMAIL PROTECTED] wrote on 08/16/2006
08:22:03 AM:
Earl F. Glynn wrote:
[deleted]
efg
[deleted]
(I think this is recognized by d. bates, but simply way down his 'to
do'
list :-().
joerg
No doubt Doug Bates would gladly accept patches ... .
I'm having problems getting nls to agree that convergence has occurred in a
toy problem.
nls.out never gets defined when there is an error in nls. Reaching the
maximum number of iterations is alway an error, so nls.out never gets
defined when the maximum number of iterations is reched.
From
Earl F. Glynn efg at stowers-institute.org writes:
Here's my toy problem:
?nls.control
?nls
# Method 2
X - 0:15
Y - 9.452 * exp(-0.109*X) + 5.111 # Toy problem
nls.out - nls(Y ~ a*exp(b*X)+c,
+start=list(a=6,b=-0.5,c=1),
+
Dieter Menne [EMAIL PROTECTED] wrote in message
news:[EMAIL PROTECTED]
Earl F. Glynn efg at stowers-institute.org writes:
This toy problem is exactly what the warning is for:
Warning
Do not use nls on artificial zero-residual data.
Add some noise and try again.
Thank you!
I had adapted
Or, maybe there's something I don't understand about the
algorithm being used.
Indeed! So before making such comments, why don't you try to learn about it?
Doug Bates is a pretty smart guy, and I think you do him a disservice when
you assume that he somehow overlooked something that he
Berton Gunter [EMAIL PROTECTED] wrote in message
news:[EMAIL PROTECTED]
Or, maybe there's something I don't understand about the
algorithm being used.
Indeed! So before making such comments, why don't you try to learn about
it?
Doug Bates is a pretty smart guy, and I think you do him a
[EMAIL PROTECTED] wrote:
Dear list,
I do have a problem with nls. I use the following data:
test
time conc dose
0.50 5.401
0.75 11.101
1.00 8.401
1.25 13.801
1.50 15.501
1.75 18.001
2.00 17.001
2.50 13.901
3.00 11.201
3.50
Hi, Doug:
How would you diagnose something like this? For example, might
the following (from ?nlsModel) help:
DNase1 - DNase[ DNase$Run == 1, ]
mod -
nlsModel(density ~ SSlogis( log(conc), Asym, xmid, scal ),
DNase1, start=list( Asym = 3, xmid = 0, scal = 1 ))
Dear list,
I do have a problem with nls. I use the following data:
test
time conc dose
0.50 5.401
0.75 11.101
1.00 8.401
1.25 13.801
1.50 15.501
1.75 18.001
2.00 17.001
2.50 13.901
3.00 11.201
3.50 9.901
4.00 4.70
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