Hi,
I'm attempting to calculate the 0.25 and 0.97 quantiles for tree height (0-50
meters) against tree age (0-300 years) and I am running into some difficulty
with the plotted grafic. I've run the examples in the quantreg help and can get
those to work properly and by plugging in my data I can also get the lines
plotted on my dataset. Unfortunately I'm running into a problem with the median
and other regression lines with tree age younger than 50 years, basically the
median is in this range overestimated and even comes out of the rage of
oberservations. here is the code I'm using.
# then fit the median using nlrq
spruce.nlrq <- nlrq(height ~ SSlogis(age, Asym, mid, scal),data=spruce,
tau=0.5, trace=TRUE)
lines(1:200, predict(spruce.nlrq, newdata=list(age=1:200)), col="2")
I believe this has something to do with the SSlogis, as this gives the
parameters for an S curve. My data set does not have the typical S curve
shape, instead you could image it as starting at the inflection point of an S
curve. This is what I expect the .025 quantile to be similar to:
x <- seq(1,100,1)
plot(log(x))
the 0,975 should also have a logarithmic shape but no such a steep incline.
Ive tried using different self starting models as found under:
apropos("^ss")
however I have not gotten them to work, or at least to fix the problem. Curves
similar to mine look like these site index curves:
http://www.extension.umn.edu/distribution/naturalresources/components/3473-13.html
In the example from the nlrq help the lines of the median and the various
quantiles all start from the same location, tha is basically (x=0, y=0) in the
coodinate plane. With my problem, the lines start to be drawn from various
different positions ( the lines always start at age(x)=0, but the height(y) can
range between 0 and 15).
Additionally, the data set is quite large. with about 50,000 oberservations on
age and height.
Does anyone have a suggestion on how to fix this problem?
Thanks in advance
Dan
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