On Thu, Mar 14, 2013 at 5:07 AM, meng <laomen...@163.com> wrote:
> Hi,all:
> I met a problem of nls.
>
> My data:
> x y
> 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 the reason for the error.
> Any suggesions are welcome.
>
The gradient is singular at your starting value so you will have to
use a better starting value. If d = 0 then its linear in log(y) so
you can compute a starting value using lm like this:
lm1 <- lm(log(y) ~ x, DF)
st <- setNames(c(coef(lm1), 0), c("a", "b", "d"))
Also note that you are trying to fit a model with 3 parameters to only
4 data points.
--
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