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 [[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.