> -----Original Message----- > From: r-devel-boun...@r-project.org > [mailto:r-devel-boun...@r-project.org] On Behalf Of Vadim Ogranovich > Sent: Monday, March 14, 2011 10:37 AM > To: 'r-devel@r-project.org' > Subject: [Rd] discrepancy between lm and MASS:rlm > > Dear R-devel, > > There seems to be a discrepancy in the order in which lm and > rlm evaluate their arguments. This causes rlm to sometimes > produce an error where lm is just fine.
It may not be a problem with the order of evaluation. rlm() might not be calling model.frame() with drop.unused.levels=TRUE. I've made that mistake before with similar symptoms. Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com > > Here is a little script that illustrate the issue: > > > library(MASS) > > ## create data > > n <- 100 > > dat <- data.frame(x=rep(c(-1,0,1), n), y=rnorm(3*n)) > > > > ## call lm, works fine > > summary(lm(y ~ as.factor(x), data=dat, subset=x!=0)) > > Call: > lm(formula = y ~ as.factor(x), data = dat, subset = x != 0) > > Residuals: > Min 1Q Median 3Q Max > -2.60619 -0.82160 0.06307 0.65501 2.56677 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 0.061010 0.100027 0.610 0.543 > as.factor(x)1 0.001332 0.141459 0.009 0.992 > > Residual standard error: 1 on 198 degrees of freedom > Multiple R-squared: 4.479e-07, Adjusted R-squared: -0.00505 > F-statistic: 8.868e-05 on 1 and 198 DF, p-value: 0.9925 > > > ## call rlm, error > > summary(rlm(y ~ as.factor(x), data=dat, subset=x!=0)) > Error in rlm.default(x, y, weights, method = method, > wt.method = wt.method, : > 'x' is singular: singular fits are not implemented in rlm > > > > > My guess is that rlm first converts x to a factor, which > becomes a three-level factor, then subsets on x!=0, which > effectively eliminates a level, and then creates a > "regression" matrix, which becomes singular due to the > absence of data for a level. > > Is there a simple way to work around it. The simplest I could > think of is > with(subset(dat, x!=0), rlm(y ~ as.factor(x)) > which is ok, but most of my scripts make use of data arg to > regressions and I'd like to stay consistent as much as practical. > > Thanks, > Vadim > > > Note: This email is for the confidential use of the named > addressee(s) only and may contain proprietary, confidential > or privileged information. If you are not the intended > recipient, you are hereby notified that any review, > dissemination or copying of this email is strictly > prohibited, and to please notify the sender immediately and > destroy this email and any attachments. Email transmission > cannot be guaranteed to be secure or error-free. Jump > Trading, therefore, does not make any guarantees as to the > completeness or accuracy of this email or any attachments. > This email is for informational purposes only and does not > constitute a recommendation, offer, request or solicitation > of any kind to buy, sell, subscribe, redeem or perform any > type of transaction of a financial product. > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel > ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
