All -
My question is a bit involved, so bear with me.
I have some data that looks like:
Lake LL LW
81 2.176091259 1.342422681
81 2.176091259 1.414973348
81 2.176091259 1.447158031
81 2.181843588 1.414973348
81 2.181843588 1.447158031
81 2.184691431 1.462397998
81 2.187520721 1.447158031
81 2.187520721 1.477121255
81 2.187520721 1.505149978
...
[truncated]
I'm trying to:
1) fit a simple lm(LW~LL)
2) calculate the dffits for those data points
3) remove those data points that are 2*sqrt(p/n) (where p=the number of
parameters and n=number of data points; p=3 in a linear model, correct?
Intercept, slope, and error term?)
4) rerun the model MINUS those data points
5) compare the two lm()
Now, each of these steps I can do seperately, but only by outputting the
dffits to a .csv then removing the large dffits by hand, reading the .csv
back into R, rerunning the lm(), and comparing the first lm() to the second
lm(). I would imagine that there is a better (easier, I hope!) way to doing
all of this. Any ideas?
My programming knowledge of R is rather limited but getting better all the
time thanks to this board and the R-help archive.
Thanks,
SR
Steven H. Ranney
Graduate Research Assistant (Ph.D)
USGS Montana Cooperative Fishery Research Unit
Montana State University
P.O. Box 173460
Bozeman, MT 59717-3460
phone: (406) 994-6643
fax: (406) 994-7479
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