Having tried (with some success) to use an alternative to the QR decomposition method for fitting generalised linear models by adapting the glm and glm.fit functions, I have noticed (to be honest, become frustrated with) how glm function and its dependents keep referencing qr lists. For example the glm.summary has the surprising line covmat.unscaled <- chol2inv(object$qr$qr[p1, p1, drop = FALSE]) which seems to be an odd way of delivering the parameter (co)variance matrix. Within the glm.fit function itself, much of the code is "QR specific". Call me pedantic, but does anyone else consider that the glm function should be more omnibus?. Cheers Ross Darnell Newcastle -- -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._