# [R] nls

Peter Dalgaard p.dalgaard at biostat.ku.dk
Tue Aug 15 15:31:23 CEST 2006

```Prof Brian Ripley <ripley at stats.ox.ac.uk> writes:

> You problem is x^c for x = 0.  If you intended only c > 1, try a starting
> value meeting that condition (but it seems that the optimal c is about
> 0.27 is you increase x slightly).

Surely you mean c > 0.

>  nls(1/y ~ a+b*x^exp(c), start=list(a=1.16122,b=0.01565,c=0))
Nonlinear regression model
model:  1/y ~ a + b * x^exp(c)
data:  parent.frame()
a          b          c
0.9944025  0.1953168 -1.1495206
residual sum-of-squares:  0.03303464
>  nls(1/y ~ a+b*x^c, start=list(a=1.16122,b=0.01565,c=exp(-1.1)))
Nonlinear regression model
model:  1/y ~ a + b * x^c
data:  parent.frame()
a         b         c
0.9944026 0.1953165 0.3167891
residual sum-of-squares:  0.03303464

(but even setting c=exp(-1) triggers the error; there could be cause
for robustifying the nls algorithm)

> Why have you used ~~ ?  (Maybe because despite being asked not to, you
> sent HTML mail?)
>
> On Tue, 15 Aug 2006, Xiaodong Jin wrote:
>
> >   Is there anyway to change any y[i] value (i=2,...6) to make following NLS workable?
> >
> >   x <- c(0,5,10,15,20,25,30)
> >   y <- c(1.00000,0.82000,0.68000,0.64000,0.66667,0.68667,0.64000)
> >   lm(1/y ~~ x)
> >   nls(1/y ~~ a+b*x^c, start=list(a=1.16122,b=0.01565,c=1), trace=TRUE)
> >
> >   #0.0920573 :  1.16122 0.01565 1.00000
> > #Error in numericDeriv(form[], names(ind), env) :
> > #        Missing value or an infinity produced when evaluating the model
> >
> >
> > ---------------------------------
> >
> >
> > 	[[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>
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