2007/5/21, Lucke, Joseph F <[EMAIL PROTECTED]>: > > One issue is whether you want your estimators to be based on central > moments (covariances) or on non-central moments. Removing the intercept > changes the statistics from central to non-central moments. The > adjusted R2, by which I think you mean Fisher's adjusted R2, is based on > central moments (ratio of unbiased estimators of variances---central > moments). So if you remove the intercept, you must re-derive the > adjusted R2 for non-central moments --- you can't just plug in the > number of independent variables as zero.
I have consulted A.J. Miller's Subset Selection in Regression(1990), and I found what I was talking about adjusted R^2 was exactly as you said--Fisher's A-statisitc. The formula of adjusted R^2 without the intercept in that book was also the same as what summary(lm)$adj.r.squared does in R. I guess what you want me to derive is the formula in that book. Though I know the formula of adjusted R2 for non-central moments, I still want to know whether I am in the right way to compare *linear models with intercept and those without intercept using maximizing adjs R^2 strategy.* ** Actually, I consider the left column consisted of all 1 in predictor matrix Z as the intercept term. Then I apply maximizing adjs R^2 strategy to decide which variables to select. Z is the term in the model: Y=Zb+e. Thanks for your suggestion, and I am looking forward for your reply. -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of ??? > Sent: Sunday, May 20, 2007 8:53 PM > To: r-help@stat.math.ethz.ch > Subject: [R] How to compare linear models with intercept and those > withoutintercept using minimizing adjs R^2 strategy > > Dear R-list, > > I apologize for my many emails but I think I know how to desctribe my > problem differently and more clearly. > > My question is how to compare linear models with intercept and those > without intercept using maximizing adjusted R^2 strategy. > > Now I do it like the following: > > > library(leaps) > > n=20 > > x=matrix(rnorm(n*3),ncol=3) > > b=c(1,2,0) > > intercept=1 > > y=x%*%b+rnorm(n,0,1)+intercept > > > > var.selection=leaps(cbind(rep(1,n),x),y,int=F,method="adjr2") > > ##### Choose the model with maximum adjr2 > > var.selection$which[var.selection$adjr2==max(var.selection$adjr2),] > 1 2 3 4 > TRUE TRUE TRUE FALSE > > > Actually, I use the definition of R-square in which the model is without > a intercept term. > > Is what I am doing is correct? > > Thanks for any suggestion or correction. > -- > Junjie Li, [EMAIL PROTECTED] > Undergranduate in DEP of Tsinghua University, > > [[alternative HTML version deleted]] > > ______________________________________________ > 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 > and provide commented, minimal, self-contained, reproducible code. > -- Junjie Li, [EMAIL PROTECTED] Undergranduate in DEP of Tsinghua University, [[alternative HTML version deleted]] ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.
