If rb.lm is an lm-object, I can access the error mean square as s2 <- sum(rb.lm$residuals^2)/rb.lm$df.residual This seems a bit like hard work for such a commonly wanted quantity. Is there a better way to do this? Murray Jorgensen Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj at waikato.ac.nz Fax +64-7 838 4155 Phone +64-7 838 4773 home phone +64-7 856 6705 Mobile +64-21 139 5862 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- 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 _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Error mean square
3 messages · Murray Jorgensen, Brian Ripley
On Tue, 18 Sep 2001, Murray Jorgensen wrote:
If rb.lm is an lm-object, I can access the error mean square as s2 <- sum(rb.lm$residuals^2)/rb.lm$df.residual This seems a bit like hard work for such a commonly wanted quantity. Is there a better way to do this?
For a model without weights summary(rb.lm)$sigma^2 or deviance(rb.lm)/df.residual(rb.lm) BTW, I don't really know what you mean by `error mean square' (I would say `residual mean square'), but suspect that when weights are involved you want the weighted form which each of these compute.
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
At 06:56 AM 18-09-01 +0100, Prof Brian D Ripley wrote:
On Tue, 18 Sep 2001, Murray Jorgensen wrote:
If rb.lm is an lm-object, I can access the error mean square as s2 <- sum(rb.lm$residuals^2)/rb.lm$df.residual This seems a bit like hard work for such a commonly wanted quantity. Is there a better way to do this?
For a model without weights summary(rb.lm)$sigma^2 or deviance(rb.lm)/df.residual(rb.lm)
I know that I didn't ask questions of efficiency, but these two are slower than my proposal, especially the one calling summary.
BTW, I don't really know what you mean by `error mean square' (I would say `residual mean square'), but suspect that when weights are involved you want the weighted form which each of these compute.
I can't believe that you have never heard the term `error mean square'. Do you mean that you find it ambiguous, or that it is to be deprecated for some reason? Dr Murray Jorgensen http://www.stats.waikato.ac.nz/Staff/maj.html Department of Statistics, University of Waikato, Hamilton, New Zealand Email: maj at waikato.ac.nz Fax +64-7 838 4155 Phone +64-7 838 4773 home phone +64-7 856 6705 Mobile +64-21 139 5862 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- 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 _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._