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Dear RsR list members,<br>
<br>
I somehow got stuck wth lmRob and I am sure I am missing something
and I do not know what. It is my first time using robust statistics
and I have read all your posts and pdfs recommended<br>
<br>
I think it is likely to be a newbie question. I ploted two variables
and the pictures shows a number of outliers that I want to identify
given that the main trend between those two measurements is
positive. (although they look like a lot, it is more or less 800
points out of 6000)<br>
<br>
<br>
<img src="cid:part1.05060807.05000908@uab.cat" alt="" width="348"
height="348"><br>
<br>
<br>
I used then <br>
<br>
robust<-lmRob(WPROB~NPP,data=a)<br>
<br>
<br>
lmRob(formula = WPROB ~ NPP, data = a)<br>
<br>
Coefficients:<br>
(Intercept) NPP <br>
499.86274538 -0.00990502 <br>
<br>
Degrees of freedom: 6002 total; 6000 residual<br>
Residual standard error: 250.3199 <br>
<br>
1) I do not really understand the slope of the regression, why is it
negative???<br>
<br>
then used plot.lmRob(robust) and choose for option 11 (scatter plot
with fits)<br>
<br>
<img src="cid:part2.09040304.01070000@uab.cat" alt="" width="191"
height="191"><br>
<br>
What is meant to be the x axis (WPROB) turns into the y axis.<br>
The regression line and the confidence intervals shown have nothing
to do, of course, with the coefficients retrieved...what am I doing
wrong?<br>
<br>
Thank you in advance, <br>
<br>
pep<br>
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