[R] NLS plinear question
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 01132.0 1 630.5 21371.5 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 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] NLS plinear question
recall that 0 ^{-.2} = 1/0^{.2}, and that dividing by 0 gives Inf.
so when 0 is in trl, part of your model for RT is Inf:
trl - 0:14
p - -.2
cbind(1,trl, trl^p)
trl
[1,] 1 0 Inf
[2,] 1 1 1.000
[3,] 1 2 0.8705506
[4,] 1 3 0.8027416
[5,] 1 4 0.7578583
[6,] 1 5 0.7247797
[7,] 1 6 0.6988271
[8,] 1 7 0.6776109
[9,] 1 8 0.6597540
[10,] 1 9 0.6443940
[11,] 1 10 0.6309573
[12,] 1 11 0.6190439
[13,] 1 12 0.6083643
[14,] 1 13 0.5987029
[15,] 1 14 0.5898946
On Tue, 6 May 2008, Rick DeShon wrote:
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
01132.0
1 630.5
21371.5
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
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] NLS plinear question
0^(-0.2) = Inf, so you started with an infinite prediction for your first point and hence an infinite sum of squares. On Tue, 6 May 2008, Rick DeShon wrote: 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 01132.0 1 630.5 21371.5 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 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
