

Hi R experts,
I'm trying to use nls() for a piecewise linear regression with the first
slope constrained to 0. There are 10 data points and when it does converge
the second slope is almost always over estimated for some reason. I have
many sets of these 10point datasets that I need to do. The following
segment of code is an example, and sorry for the overly precise numbers,
they are just copied from real data.
y1<c(2.37700445, 1.76209775, 0.09795576, 2.21834963, 6.62262243,
15.70471269, 21.92956392, 36.39401717, 32.43620195, 44.77442277)
x1<c(24.6, 28.9, 33.2, 37.6, 42.0, 46.4, 50.9, 55.3, 59.8, 64.3)
dat < data.frame(x1,y1)
nlmod < nls(y1 ~ ifelse(x1 < xint+(yint/slp), yint, yint +
(x1(xint+(yint/slp)))*slp),
data=dat, control=list(minFactor=1e5,maxiter=500,warnOnly=T),
start=list(xint=39.27464924, yint=0.09795576, slp=2.15061064),
na.action=na.omit, trace=T)
##plotting the function
plot(dat$x1,dat$y1)
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])
As you can see from the plot, the line is above all data points on the
second segment. This seems to be the case for different datasets. I'm
wondering if anyone can help me understand why this happens. Is this because
there are too few data points or is it because the likelihood function is
just not smooth enough?
Karen
[[alternative HTML version deleted]]
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Try reparameterizing:
nlmod2 < nls(y2 ~ pmax(1/p, (x2  xint)), data = dat,
start = list(xint = 40.49782, p = 1), trace = TRUE, alg = "plinear")
On Mon, Apr 19, 2010 at 11:32 AM, Karen Chang Liu < [hidden email]> wrote:
> Hi R experts,
>
> I'm trying to use nls() for a piecewise linear regression with the first
> slope constrained to 0. There are 10 data points and when it does converge
> the second slope is almost always over estimated for some reason. I have
> many sets of these 10point datasets that I need to do. The following
> segment of code is an example, and sorry for the overly precise numbers,
> they are just copied from real data.
>
> y1<c(2.37700445, 1.76209775, 0.09795576, 2.21834963, 6.62262243,
> 15.70471269, 21.92956392, 36.39401717, 32.43620195, 44.77442277)
> x1<c(24.6, 28.9, 33.2, 37.6, 42.0, 46.4, 50.9, 55.3, 59.8, 64.3)
>
> dat < data.frame(x1,y1)
> nlmod < nls(y1 ~ ifelse(x1 < xint+(yint/slp), yint, yint +
> (x1(xint+(yint/slp)))*slp),
> data=dat, control=list(minFactor=1e5,maxiter=500,warnOnly=T),
> start=list(xint=39.27464924, yint=0.09795576, slp=2.15061064),
> na.action=na.omit, trace=T)
>
> ##plotting the function
> plot(dat$x1,dat$y1)
> 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])
>
> As you can see from the plot, the line is above all data points on the
> second segment. This seems to be the case for different datasets. I'm
> wondering if anyone can help me understand why this happens. Is this because
> there are too few data points or is it because the likelihood function is
> just not smooth enough?
>
> Karen
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/rhelp> PLEASE do read the posting guide http://www.Rproject.org/postingguide.html> and provide commented, minimal, selfcontained, reproducible code.
>
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/rhelpPLEASE do read the posting guide http://www.Rproject.org/postingguide.htmland provide commented, minimal, selfcontained, reproducible code.


On Mon, 19 Apr 2010, Karen Chang Liu wrote:
> Hi R experts,
>
> I'm trying to use nls() for a piecewise linear regression with the first
> slope constrained to 0. There are 10 data points and when it does converge
> the second slope is almost always over estimated for some reason. I have
> many sets of these 10point datasets that I need to do. The following
> segment of code is an example, and sorry for the overly precise numbers,
> they are just copied from real data.
>
> y1<c(2.37700445, 1.76209775, 0.09795576, 2.21834963, 6.62262243,
> 15.70471269, 21.92956392, 36.39401717, 32.43620195, 44.77442277)
> x1<c(24.6, 28.9, 33.2, 37.6, 42.0, 46.4, 50.9, 55.3, 59.8, 64.3)
>
> dat < data.frame(x1,y1)
> nlmod < nls(y1 ~ ifelse(x1 < xint+(yint/slp), yint, yint +
> (x1(xint+(yint/slp)))*slp),
> data=dat, control=list(minFactor=1e5,maxiter=500,warnOnly=T),
> start=list(xint=39.27464924, yint=0.09795576, slp=2.15061064),
> na.action=na.omit, trace=T)
>
> ##plotting the function
> plot(dat$x1,dat$y1)
> 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])
>
> As you can see from the plot, the line is above all data points on the
> second segment. This seems to be the case for different datasets. I'm
> wondering if anyone can help me understand why this happens. Is this because
> there are too few data points or is it because the likelihood function is
> just not smooth enough?
>
I think there's something wrong with your graph. If I do
points(x1,fitted(nlmod),col="red")
I get points that are on the horizontal line segment, but then go through the data nicely on the right.
thomas
Thomas Lumley Assoc. Professor, Biostatistics
[hidden email] University of Washington, Seattle
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/rhelpPLEASE do read the posting guide http://www.Rproject.org/postingguide.htmland provide commented, minimal, selfcontained, reproducible code.

