[R] Advice on picking a regression method

[Dewez Thomas]

Dear R-users,

There are tons of methods out there for fitting independant variables to a
dependent variable. All stats books tell you about the assumptions behind
OLS (ordinary least squares) and warn against abusive use of the method
(which many of us do disregard by lack of a better knowledge). Most
introductory text books stop there and don't tell you what the next best
option might be. I am aware that there might be many depending on the type
of study so here are the data to sort this question out.

In this instance, I am performing a regression on observations whose
residuals show heteroscedasticity (the variance of residuals is small for
small dependant variable values and increases for larger ones), which
violates one assumption of the OLS method. Which of the numerous options
should I choose? glm, robust lm, ...

The problem is kept simple for now. I only try to explain the log of local
topographic slope (dependent variable) with regard to the distance to the
outlet of a catchment (independent variable) for a fixed drained area. Both
variables are continuous.

I ordered Venables and Ripley 2002, which I suspect is a sound reading for
advanced stats with R, but it has not arrived yet and I need to move on
asap. Any advice or pointer to the appropriate literature is greatly
appreciated.

Thomas

Dr Thomas Dewez
ENTEC Post-Doctoral Fellow 
ARN - MAS
BRGM (French Geological Survey)
3 Av. C. Guillemin
45000 Orleans - France

Phone: +33 (0)2 38644606
Fax: +33 (0)2 38643361
***
Le contenu de cet e-mail et de ses pièces jointes est destin...{{dropped}}