Dear Simon, I'm not sure that I follow this entirely, but if error variance decreases with the level of the response, you could try raising the response to a power greater than 1. Of course, the response has to be non-negative. You might take a look at the spread.level.plot function in the car package, which will produce a suggested transformation when applied to an lm object.
I hope that this helps, John > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Simon Chamaill� > Sent: Tuesday, April 13, 2004 12:36 PM > To: [EMAIL PROTECTED] > Subject: [R] Non-homogeneity of variance - decreasing variance > > Hello all, > I'm running very simple regression but face a problem of > non-homogeneity of variance, but with a decreasing variance > with increasing mean...I do not know how to deal with that. > this relationship doesn't seem to be strong, but it's my > first time to see something like that, and would like to know > what to do if one day it becomes stronger. I tested just for > fun some transformation but was not able to get a better > model. I do not know if it can help, but my predictor > variable is a kind of gamma poisson-shaped-like zero-rich > distribution (continuous of course), highly overdispersed. > If one know how to deal with decreasing variance, I would > appreciate any advice (I tried to modelize negative > variance-mean relationship in a new > quasi- family this was prohibited, only constant, mu, mu^x > (and mu(1-mu) for > binomial) were allowed). I've definitively reached the border > of the statistical black box for me. > thanks > simon > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
