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 <[email protected]>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
>
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