Dear R users, Usually the variance-inflation factor, which is based on R^2, is used as a measure for multicollinearity. But, in contrast to OLS regression there is no robust R^2 available for MM-regressions in R. Do you know if an equivalent or an alternative nmeasure of multicollinearity is available for MM-regression in R? With best regards, Carsten Colombier Dr. Carsten Colombier Economist Group of Economic Advisers Swiss Federal Finance Administration Bundesgasse 3 CH-3003 Bern phone +41 31 322 63 32 fax +41 31 323 08 33 email: carsten.colombier at efv.admin.ch www.efv.admin.ch
mutlicollinearity and MM-regression
3 messages · Carsten.Colombier@efv.admin.ch, Brian Ripley, John Hendrickx
On Mon, 16 Aug 2004 Carsten.Colombier at efv.admin.ch wrote:
Dear R users, Usually the variance-inflation factor, which is based on R^2, is used as a measure for multicollinearity.
I disagree, strongly, that this is `usual' practice.
But, in contrast to OLS regression there is no robust R^2 available for MM-regressions in R. Do you know if an equivalent or an alternative nmeasure of multicollinearity is available for MM-regression in R?
?kappa .
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
--- Carsten.Colombier at efv.admin.ch wrote:
Dear R users, Usually the variance-inflation factor, which is based on R^2, is used as a measure for multicollinearity. But, in contrast to OLS regression there is no robust R^2 available for MM-regressions in R. Do you know if an equivalent or an alternative nmeasure of multicollinearity is available for MM-regression in R?
I'm not sure what MM-regression is. But I've just put a general purpose tool for evaluating collinearity on my website. See http://www.xs4all.nl/~jhckx/R/perturb/ The perturb programs works by adding small random changes (perturbations) to selected variables. Categorical variables are randomly misclassified. This process is repeated a specified number of times, after which the impact of the perturbations on parameter stability can be evaluated. It should work with any R-procedure that has a formula. The package also contains colldiag, for calculating condition indexes and variance decomposition proportions. Since this only works on the independent variables, it should work for your problem as well. Feedback welcomed. I plan to submit the package to CRAN in a few days, after I get the help files updated