[R] Problems running a 4-parameter Weibull function with nls

[Spencer Graves]

      Might "nls" be testing values for "lag" that exceed min(X)?  That 
might produce the error you observe. 

      I routine reparameterize problems like this to send boundaries to 
Inf, e.g.: 

      x0 <- min(df$X)     
      fit<-nls(Y ~ max.*(1 - 
exp(-(rate*(X-x0+exp(ln.lag)))^shape)),df,start=start.est, x0=x0)
      ##NOT TESTED

      (Also, I try to avoid conficts between objects / variables I use 
and, e.g., standard system functions like "max" and "df".  R can 
determine whether a function or a non-function is required in most but 
not all contexts.) 

      hope this helps. 
      spencer graves

Mike Saunders wrote:

>Hi,
>
>I am rather new to R, but both myself and another much more experience user cannot figure this out.  I have a collegue who has a 800+ nonlinear regressions to run for seed germination (different species, treatments, etc.) over time.  I created a looping structure to extract the parameters from each regression; I will then use the parameters themselves for further analysis.  I would like to fit a 4-parameter, sigmoidal shape Weibull because it it paramatized to have a maximum germination rate (max), a time lag for the start of germination (lag), a germination rate (rate) and a shape parameter (shape).
>
>Here is a copy of this bit of the code:
>
>start.est=list(max=max(df$Y),rate=1/(df$X[tx]-((df$X[tz-1]+df$X[tz])/2)),
>    lag=(df$X[tz-1]+df$X[tz])/2,shape=1.1)
>nls.control(maxiter=1000,minFactor=1/8192)
>fit<-nls(Y ~ max*(1 - exp(-(rate*(X-lag))^shape)),df,start=start.est)
>
>
>Here is one column of the data (X=Julian day, Y = % germination):
>
>       X        Y
>1   111 0.0000000
>2   125 0.0000000
>3   131 0.0000000
>4   138 0.3076923
>5   145 0.4260355
>6   152 0.4733728
>7   159 0.5443787
>8   166 0.5680473
>9   173 0.5680473
>10  180 0.5917160
>11  187 0.5917160
>12  194 0.5917160
>13  201 0.6153846
>14  208 0.6153846
>15  215 0.6153846
>16  223 0.6153846
>17  229 0.6153846
>18  236 0.6153846
>19  245 0.6153846
> 
>Here is the error I keep getting:
>
>Error in numericDeriv(form[[3]], names(ind), env) : 
>        Missing value or an Infinity produced when evaluating the model
>
>
>I have tried these things to get this to work:
>    1) Mess with the starting values quite a bit
>    2) Seed the regression with linear estimates between my known points (i.e., figure         out daily averages).  I then wanted to regress on these to get starting estimates         to use with the real data.
>    3) Drop out all the 0s in the seeded data
>    4) Add jitter to the seeded data
>I should note that this worked to get a 3-parameter Gompertz to work, but that functional form is more difficult to interpret biologically.
>
>I am out of ideas.  Thoughts anyone?  I would appreciate any help.
>
>Mike Saunders
>Research Assistant
>Department of Forest Ecosystem Sciences
>University of Maine
>
>
>	[[alternative HTML version deleted]]
>
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>

-- 
Spencer Graves, PhD, Senior Development Engineer
O:  (408)938-4420;  mobile:  (408)655-4567