[Rd] problem with zero-weighted observations in predict.lm?
pdalgd at gmail.com
Thu Jul 29 10:11:53 CEST 2010
Peter Dalgaard wrote:
> Prof Brian Ripley wrote:
>> I think you will find that 'n' is used in several ways in predict.lm,
>> and since NA-handling was introduced in R 1.8.0 they may differ in
>> value. So the safest route seems to be to change just 'n' in
>> df <- n - p
> Yes, that seems to fix things. Will commit to R-devel shortly.
Spoke too soon, it fixes Bill's case, but breaks one of the regression
In fact this goes deeper, summary.lm special-cases the same zero-rank
case by using length(residuals), so it also miscalculates with zero weights:
> fit <- lm(y~0,weights=c(0,rep(1,9)))
lm(formula = y ~ 0, weights = c(0, rep(1, 9)))
Min 1Q Median 3Q Max
-1.95428 -1.40571 -0.42378 -0.05795 1.05518
Residual standard error: 1.119 on 10 degrees of freedom
Hum. lm() actually returns df.residual, AFAICS in all cases, now why
don't we just use that throughout????
Center for Statistics, Copenhagen Business School
Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
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