I decided to follow up my own suggestion and look at the robustness of
nls vs. nlxb. NOTE: this problem is NOT one that nls() would usually be
applied to. The script below is very crude, but does illustrate that
nls() is unable to find a solution in >70% of tries where nlxb (a
Marquardt approac
As Gabor indicates, using a start based on a good approximation is
usually helpful, and nls() will generally find solutions to problems
where there are such starts, hence the SelfStart methods. The Marquardt
approaches are more of a pit-bull approach to the original
specification. They grind aw
On Fri, Mar 15, 2013 at 9:45 AM, Prof J C Nash (U30A) wrote:
> Actually, it likely won't matter where you start. The Gauss-Newton direction
> is nearly always close to 90 degrees from the gradient, as seen by turning
> trace=TRUE in the package nlmrt function nlxb(), which does a safeguarded
> Mar
27 -0400
From: Gabor Grothendieck
To: meng
Cc: R help
Subject: Re: [R] question about nls
Message-ID:
Content-Type: text/plain; charset=ISO-8859-1
On Thu, Mar 14, 2013 at 5:07 AM, meng wrote:
>Hi,all:
>I met a problem of nls.
>
>My data:
>xy
>60 0.8
>80 6.5
>100
On Thu, Mar 14, 2013 at 5:07 AM, meng wrote:
> Hi,all:
> I met a problem of nls.
>
> My data:
> xy
> 60 0.8
> 80 6.5
> 100 20.5
> 120 45.9
>
> I want to fit exp curve of data.
>
> My code:
>> nls(y ~ exp(a + b*x)+d,start=list(a=0,b=0,d=1))
> Error in nlsModel(formula, mf, start, wts) :
> sin
Hi,all:
I met a problem of nls.
My data:
xy
60 0.8
80 6.5
100 20.5
120 45.9
I want to fit exp curve of data.
My code:
> nls(y ~ exp(a + b*x)+d,start=list(a=0,b=0,d=1))
Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates
I can't find out
Thanks, Ellison. Another question is if this p-value is a good parameter to
test if the fitting is good,
Absolutely not.
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Liang:
In nonlinear models especially (and more generally, also), "small" p
values are not reliable indicators of whether a fit is or is
not"good." I would strongly suggest that you consult with your local
statistician -- this is a (complicated, as it depends on the meaning
of "good") statistical
Thanks, Ellison. Another question is if this p-value is a good parameter to
test if the fitting is good, as you this test is only for the null that the
coefficient is 0 (a is 0 in y=exp(a*x), right?)?
On Thu, Feb 7, 2013 at 10:48 AM, S Ellison wrote:
>
>
> > After applying the NLS for a model l
> After applying the NLS for a model like y=exp(a*x), and I get
> a result showing the summary as:
> Estimate Std. Error t value Pr(>|t|)
> 2.6720 1.4758 1.811 0.3212
>
> My question is what this t-statistics tests? And what's the
> meaning of Pr?
t is (estimate/std.err) and can be us
After applying the NLS for a model like y=exp(a*x), and I get a result
showing the summary as:
Estimate Std. Error t value Pr(>|t|)
2.6720 1.4758 1.811 0.3212
My question is what this t-statistics tests? And what's the meaning of Pr?
New to R. Thanks.
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