[Rd] discrepancy between lm and MASS:rlm

[Vadim Ogranovich]

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.

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.