Hello

I was trying to estimate the weibull model using nls after putting OLS
values as the initial inputs to NLS.
I tried multiple times but still i m getting the same error of Error in
nlsModel(formula, mf, start, wts) :
  singular gradient matrix at initial parameter estimates.

The Program is as below

> vel <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14)
> df <- data.frame(conc, vel)
> df
      conc vel
1    0.077   1
2    0.328   2
3    0.882   3
4    1.195   4
5    1.884   5
6    3.577   6
7    6.549   7
8   13.000   8
9   33.690   9
10  52.220  10
11  90.140  11
12 166.050  12
13 233.620  13
14 346.890  14
> plot(df$vel, df$conc)
> para0.st <- c(K=450,
+       alpha=0.054,beta=3.398 )
>  fit0 <- nls(
+      conc~ K-(K*exp(-(vel/alpha)^beta)), df, start= para0.st,trace=T)
Error in nlsModel(formula, mf, start, wts) :
  singular gradient matrix at initial parameter estimates


I will be highly thankful if some one can please let me know where is the
mistake as i m unable to trace it.

Thanks
Ruchita

On Wed, Dec 16, 2009 at 3:18 PM, ruchita gupta <ruchitarg...@gmail.com>wrote:

> Hello
>
> After performing NLS estimates for some sigmoid model(like logistic growth
> model  and Gompertz growth models), how can we get the RMSE(root mean square
> error) and MAPE(mean absolute percentage error) in  R statistical tool for
> comparison between two models
>
> Thanks
> Ruchita
>

        [[alternative HTML version deleted]]

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