[R] plot regression line, log-transformation
JRadinger at gmx.at
Mon Sep 5 13:07:00 CEST 2011
I've somehow general questions.
I've got a dataset which shows signs of heteroscedasticity and non-normality in errors if I do a normal linear regression of the form Y~X. So to things came into my mind, either transforming the variables (log or log10) or using robust regression. So my first question:
How can I decide what is the better method? Either: lm(log(Y)~log(X)) or rlm(Y~X)? Or is it even necessary to log transform for the robust regression?
Another question has to do with the plotting:
I can do a simple scatterplot with plot(Y~X) but that doesn't give a good picture as lot of the points are clumped in the left down corner. So I thought I could use either: plot(Y~X,log="xy") or plot(log(Y)~log(X)) but then I have problems if I want to plot also the abline from the robust regression (which is then probably not a straight line anymore). How do you deal with such cases where the plot uses different scaling (log) then the regression (and therefore the abline).
Thank you very much!
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