This only uses 2 parameters instead of 3 and gives quite a good fit:
> DF <- structure(list(conc = c(0.077, 0.328, 0.882, 1.195, 1.884, 3.577,
+ 6.549, 13, 33.69, 52.22, 90.14, 166.05, 233.62, 346.89), vel =
1:14), .Names = c("conc",
+ "vel"), class = "data.frame", row.names = c(NA, -14L))
>
> DF.nls <- nls(conc ~ a * exp(b/vel), DF, start = c(a=1, b=1))
> DF.nls
Nonlinear regression model
model: conc ~ a * exp(b/vel)
data: DF
a b
35773.97 -65.02
residual sum-of-squares: 249.6
Number of iterations to convergence: 12
Achieved convergence tolerance: 1.410e-06
> plot(conc ~ vel, DF)
> lines(DF$vel, fitted(DF.nls))
On Fri, Dec 18, 2009 at 7:53 AM, ruchita gupta <ruchitarg...@gmail.com> wrote:
> Hello
>
> I was trying to estimate the weibull model using nls after putting OLS
> values as the initial inputs to NLS.
> I tried multiple times but still i m getting the same error of Error in
> nlsModel(formula, mf, start, wts) :
> singular gradient matrix at initial parameter estimates.
>
> The Program is as below
>
>> vel <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14)
>> df <- data.frame(conc, vel)
>> df
> conc vel
> 1 0.077 1
> 2 0.328 2
> 3 0.882 3
> 4 1.195 4
> 5 1.884 5
> 6 3.577 6
> 7 6.549 7
> 8 13.000 8
> 9 33.690 9
> 10 52.220 10
> 11 90.140 11
> 12 166.050 12
> 13 233.620 13
> 14 346.890 14
>> plot(df$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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> and provide commented, minimal, self-contained, reproducible code.
>
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