arivald <rzepus.m <at> gmail.com> writes:
> I am trying to fit an exponential model using nls to some data.
>
> #data
> t <- c(0,15,30,60,90,120,240,360,480)
> var <- c(0.36,9.72,15.50,23.50,31.44,40.66,59.81,73.11,81.65)
> df <- data.frame(t, var)
>
> # model
> # var ~ a+b*(1-exp(-k*t))
>
> # I'm looking for values of a,b and k
>
> # formula
> # mod <- nls(formula = var ~ a+b *(1-exp((-k)*t)), start=list(a=0, b=10,
> k=0), trace=T)
>
> # It fails and I get the following error -
> Error in nlsModel(formula, mf, start, wts) :
> singular gradient matrix at initial parameter estimates
>
Try different starting values, especially with k>0 ?
mod2 <- nls(formula = var ~ a+b *(1-exp((-k)*t)),
start=list(a=0, b=10,k=0.01), trace=TRUE)
Alternately you can try a self-starting model (see ?SSasymp),
although the parameterization is a little different.
mod3 <- nls(formula = var ~ SSasymp(t,b,a,lrc), trace=TRUE)
coef(mod2)
coef(mod3)
with(as.list(coef(mod3)),c(a=a,b=b-a,k=exp(lrc)))
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