[R] NLS plinear question

From: Rick DeShon <deshon_at_msu.edu>
Date: Tue, 06 May 2008 16:50:11 -0400


Hi All.

I've run into a problem with the plinear algorithm in nls that is confusing me.

Assume the following reaction time data over 15 trials for a single unit. Trials are coded from 0-14 so that the intercept represents reaction time in the first trial.

trl RT

 0    1132.0
 1     630.5
 2    1371.5
 3     704.0
 4     488.5
 5     575.5
 6     613.0
 7     824.5
 8     509.0
 9     791.0
10     492.5
11     515.5
12     467.0
13     556.5
14     456.0

Now fit a power function to this data using nls with the plinear algorithm
>fit.pw <-nls(RT ~ cbind(1,trl, trl^p), start = c(p = -.2), algorithm =
"plinear", data=df.one)

Yields the following error message....
"Error in numericDeriv(form[[3]], names(ind), env) :

   Missing value or an infinity produced when evaluating the model"

Now, recode trial from 1-15 and run the same model.
>fit.pw <-nls(RT ~ cbind(1,trl, trl^p), start = c(p = -.2), algorithm =
"plinear", data=df.one)

Seems to work fine now...
Nonlinear regression model
  model: RT ~ cbind(1, trl, trl^p)
   data: df.one

         p .lin1 .lin.trl .lin3    -0.2845 200.3230 -8.9467 904.7582  residual sum-of-squares: 555915

Number of iterations to convergence: 11

Any idea why having a zero for the first value of X causes this problem?

Thanks in advance,

Rick DeShon

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