Dear All,
I have made a script in R (r_nonlinear_leastsquare.R) to fit an exponential
decay curve to my data using nls module:
-
args <- commandArgs(trailingOnly = TRUE)
#"/project/dmp
Thanks to Berend for his help with this. The problems seems to have been due
to an environment that wasn't clean. I also gave x & y that were
untransformed. But I am able to get results now.
Jeff
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On 02-04-2012, at 21:20, Jeff Breiwick wrote:
> Thanks for that. Sorry, I did forget to give some basics:
>
You should also reply to the list so that other can follow the thread.
I am also sending this the list.
> Running R-1.15.0 (x64) on Windows 7.
I assume you mean R2.15.0
>
> The data
On 02-04-2012, at 20:48, Jeff Breiwick wrote:
> Hello,
>
> I am running a simple nls model (which a friend ran OK) but I get the
> following error:
>
> Error in nls(y ~ R * (1 - (x/K)^2), data = nls.dat, start = list(R = 0.3, :
> object 'R_nls_iter' not found
>
> Does anyone know what the
Hello,
I am running a simple nls model (which a friend ran OK) but I get the
following error:
Error in nls(y ~ R * (1 - (x/K)^2), data = nls.dat, start = list(R = 0.3, :
object 'R_nls_iter' not found
Does anyone know what the 'R_nls_iter' error is?
The data are:
x=1:8 ; y=c(14,19,25,34,43
Also I have this problem that many times the method converges to a local
maximum...if I run it a few times, I often get the expected answer.
Is there any way to fix this problem by changing the convergence conditions?
I have tried changing the nls.control {stats} but hasn't helped much. Any
sugges
Diviya Smith gmail.com> writes:
>
> I dont think *r* is related to the problem. I am not trying to
> estimate *r* and
> so basically I am giving the model the correct value of *r* and so log(1-r)
> should not go to infinity.
>
> For test data, I generate data from the same model and add noise
I dont think *r* is related to the problem. I am not trying to estimate *r* and
so basically I am giving the model the correct value of *r* and so log(1-r)
should not go to infinity.
For test data, I generate data from the same model and add noise (using *r
norm*), with the following parameters -
Diviya Smith wrote on 09/20/2011 01:03:22 PM:
>
> Hello there,
>
> I am using NLS for fitting a complex model to some data to estimate a
couple
> of the missing parameters. The model is -
> y ~
(C+((log(1-r))*exp(-A*d)*(-1+r+exp(d*(A-B)))/(r*(-A*d+d*B+log(1-r)
> where A, B and C are unknown
Hello there,
I am using NLS for fitting a complex model to some data to estimate a couple
of the missing parameters. The model is -
y ~ (C+((log(1-r))*exp(-A*d)*(-1+r+exp(d*(A-B)))/(r*(-A*d+d*B+log(1-r)
where A, B and C are unknown.
In order to test the model, I generate data by setting value
I've been trying to run some analysis using the nls function in R but keep
coming up with an error message which I don't understand how to fix. The
message follows here:
Error in nls(formula = f.p, data = n.data, start = list(S = 1, a = -0.1, :
singular gradient
In addition: Warning messages
On 2010-07-09 13:29, Duncan Murdoch wrote:
On 09/07/2010 2:36 PM, Jim Bouldin wrote:
> 1. The expression you gave us is clearly not the one that produced
the > error: it involved "ring.area" and "ba.beg".
> > 2. You don't tell us what x and y are, so we can't reproduce
anything.
Sorry, I guess
On 09/07/2010 2:36 PM, Jim Bouldin wrote:
> 1. The expression you gave us is clearly not the one that produced the
> error: it involved "ring.area" and "ba.beg".
>
> 2. You don't tell us what x and y are, so we can't reproduce anything.
Sorry, I guess that was unclear. I changed the respon
> 1. The expression you gave us is clearly not the one that produced the
> error: it involved "ring.area" and "ba.beg".
>
> 2. You don't tell us what x and y are, so we can't reproduce anything.
Sorry, I guess that was unclear. I changed the response and independent
variable names to y and
On 09/07/2010 1:51 PM, Jim Bouldin wrote:
I am trying to perform an nls for a valid negative exponential function:
zz=nls(y~constant+a.est*2.7183^(b.est*x),start=list(constant=4.0,a.est=-4,b.est
= -.005),trace=T)
and am getting a number of different error messages, the most problematic
of whic
I am trying to perform an nls for a valid negative exponential function:
zz=nls(y~constant+a.est*2.7183^(b.est*x),start=list(constant=4.0,a.est=-4,b.est
= -.005),trace=T)
and am getting a number of different error messages, the most problematic
of which is "Error in nls(ring.area ~ constant + a
Jim Bouldin wrote:
When I try to run the following non-linear regression with variables
index1 and prl3:
beta = 4
nls(index1~beta*(1/prl3),start = list(beta = 4))
I get this error message:
Error in nls(index1 ~ beta * (1/prl3), start = list(beta = 4)) :
REAL() can only be applied to a
When I try to run the following non-linear regression with variables
index1 and prl3:
> beta = 4
> nls(index1~beta*(1/prl3),start = list(beta = 4))
I get this error message:
Error in nls(index1 ~ beta * (1/prl3), start = list(beta = 4)) :
REAL() can only be applied to a 'numeric', not a 'lo
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