What concerns me about this is if people call the summary methods directly on objects not of the right class. That used to be quite prevalent in R itself, but problems with residuals/weights mean it has now gone, I believe.
summary.lm and summary.glm are exported from stats, and this indicates that they were quite widely used (and a grep across CRAN suggests that they still are). One fairly backwards-compatible option would seem to be to call the vcov generic only if the object inherits from [g]lm and had an earlier class. On Wed, 27 Dec 2006, Thomas Lumley wrote: > > There has been recent discussion about alternatives to the model-based > standard error estimators for lm. While some people like the sandwich > estimator and others don't, it is clear that neither estimator dominates > the other for any sane loss function. It is also worth noting that the > sandwich estimator is the default for t.test(). > > I think it would be useful for models using other variance estimators to > be able to inherit from lm and use summary.lm and predict.lm (and > similarly for glm). The main step in making this possible would be > moving the variance-covariance matrix computation that is currently > duplicated in summary.lm and predict.lm into vcov.lm, and then having > summary.lm and predict.lm call vcov(). > > This allows a fitting function (whether lm() or another function) to > produce objects that inherit usefully from lm and glm but have other > standard error estimators, by supplying a new vcov method for the class. > The initial discusssion was about heteroscedasticity-consistent sandwich > estimators, but from my point of view autocorrelation-consistent > estimators and estimators that handle sampling weights are more > interesting. > > OOP purists might point out that the relationship involved is not, > strictly speaking, inheritance. They would be quite right. However, > unless someone wants to rewrite glm and lm for S4 classes I think that > battle is lost. > > > -thomas > > Thomas Lumley Assoc. Professor, Biostatistics > [EMAIL PROTECTED] University of Washington, Seattle > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel > -- Brian D. Ripley, [EMAIL PROTECTED] 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 ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
