I did mean to use x1,x2,x3,x4 in the new data frame. And I think the theory would be something like
yhat = 1' K' bhat and so the variance should be 1' K'CK 1 where C=(X'X)-1 and 1 is a 1 vector. The question is do I need to form these matrices and grind through it or is there an easier way? Bill -----Original Message----- From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] Sent: Tuesday, May 02, 2006 2:54 PM To: Christos Hatzis Cc: 'Bill Szkotnicki'; 'R-Help help' Subject: Re: [R] predict.lm On Tue, 2 May 2006, Christos Hatzis wrote: > I think you got it right. > > The mean of the (weighted) sum of a set of random variables is the > (weighted) sum of the means and its variance is the (weighted) sum of the > individual variances (using squared weights). Here you don't have to worry > about weights. > > So what you proposed does exactly this. Yes, but the theory has assumptions which are not met here: the random variables are correlated (in almost all case). > -Christos > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Bill Szkotnicki > Sent: Tuesday, May 02, 2006 2:59 PM > To: 'R-Help help' > Subject: [R] predict.lm > > I have a model with a few correlated explanatory variables. > i.e. >> m1=lm(y~x1+x2+x3+x4,protdata) > and I have used predict as follows: > >> x=data.frame(x=1:36) >> yp=predict(m1,x,se.fit=T) How can this work? You fitted the model to x1...x4 and supplied x. >> tprot=sum(yp$fit) # add up the predictions tprot > > tprot is the sum of the 36 predicted values and I would like the se of that > prediction. > I think >> sqrt(sum(yp$se.fit^2)) > is not correct. > > Would anyone know the correct approach? > i.e. How to get the se of a function of predicted values (in this case sum) You need to go back to the theory: it is easy to do for a linear function, otherwise you will need to linearize. -- 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-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html