Thank you both.
Katharine approach seemed to me easier to implement so I used it
successfully. However I still wonder why in linear model using lm I can
use
for (i in ) lm( data[,i]~data[,1])
but in nls the same construction fails. I understand that it is sometimes
difficult to set
Thank you Berwin.
Ok, I take your point. I normally do nls modelling interactively but this
time I was given a set of data so I tried to use an approach which I use
quite often in lm or in plotting to pdf file. I obviously was not
successful and there is nothing about it in documentation or
As has already been pointed out, the syntax of formulae in nls() is not
the same as in linear models. So things which are valid for linear models
are not necessarily valid for others.
Since nls() is sparsely documented on the help page, you need to look at
the references (and you can also
Dear all
Nobody responded to my previous post so far so I try with more offending
subject.
I just encountered a strange problem with nls formula. I tried to use nls
in cycle but I was not successful. I traced the problem to some parse
command.
Here is an example
DF-data.frame(x=1:10,
Dear Petr,
I think it's a feature. the formula interface also won't let you specify
the slots of S4 objects in the model spec.
How about
coef(nls(y~a*x^b, data=list(x=DF[,1], y=DF[,2]), start=list(a=3, b=.7)))
?
On Thu, 26 Jun 2008, Petr PIKAL wrote:
Dear all
Nobody responded to my
Try this and note, in particular, that the model: line
in the output has the correct variables substituted:
nm - names(DF)
eqn - sprintf(%s ~ a * %s, nm[2], nm[1])
nls(eqn, DF, start = c(a = 1))
Nonlinear regression model
model: y ~ a * x
data: DF
a
1.133
residual sum-of-squares:
G'day Petr,
On Thu, 26 Jun 2008 13:57:39 +0200
Petr PIKAL [EMAIL PROTECTED] wrote:
I just encountered a strange problem with nls formula. I tried to use
nls in cycle but I was not successful. I traced the problem to some
parse command.
[...]
I am not sure if this behaviour is a bug or
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