[RsR] robust scatterplot with fits

Dear RsR list members,

  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

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)





I used then

robust<-lmRob(WPROB~NPP,data=a)


lmRob(formula = WPROB ~ NPP, data = a)

Coefficients:
  (Intercept)          NPP
499.86274538  -0.00990502

Degrees of freedom: 6002 total; 6000 residual
Residual standard error: 250.3199

1) I do not really understand the slope of the regression, why is it 
negative???

then used plot.lmRob(robust) and choose for option 11 (scatter plot with 
fits)



What is meant to be the x axis (WPROB) turns into the y axis.
The regression line and the confidence intervals shown have nothing to 
do, of course, with the coefficients retrieved...what am I doing wrong?

Thank you in advance,

pep

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