Hi,
I have a small dataset that I'm fitting a segmented
regression using nls on. I get a step below minimum factor error, which I
presume is because residual sum of square is still "not small enough"
when steps in the parameter space is already below specified/default
value. However, when I look at the trace, the convergence seems to have
been reached. I initially thought I might have reached the parameter
space boundary, but these converging parameter values are by no means
near boundary, they are quite in the middle. Could someone help me
understand or throw out some possibilities?
##Here's a sample dataset and code.
y2<-c(2.404529, 1.625661,
1.013981, 3.810921, 10.023745, 10.990817, 10.740636,
11.246827,17.022761, 21.430386)
x2<-c(25.0, 29.3, 33.8, 38.3,
42.8, 47.2, 51.6, 55.8, 60.4, 64.9)
dat <- data.frame(x2,y2)
nlmod <- nls(y2 ~ ifelse(x2 <
xint+(yint/slp), yint, yint + (x2-(xint+(yint/slp)))*slp),
data=dat, control=list(minFactor=1e-5,maxiter=500,warnOnly=T),
start=list(xint=40.49782, yint=1.013981, slp=0.8547828),
na.action=na.omit, trace=T)
##plotting the function
plot(dat$x2,dat$y2)
segments(x0=0,
x1=coef(nlmod)[1]+coef(nlmod)[2]*coef(nlmod)[3],
y0=coef(nlmod)[2], y1=coef(nlmod)[2])
segments(x0=coef(nlmod)[1]+coef(nlmod)[2]*coef(nlmod)[3],x1=80,
y0=coef(nlmod)[2], y1=80*coef(nlmod)[3]+coef(nlmod)[2])
Karen
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