This bug is not quite fixed - the example from my original report now =
works using R-2.2.1, but
plot(Uniform, 6)
does not. The bug is due to
if (show[6]) {
ymx <- max(cook, na.rm =3D TRUE) * 1.025
g <- hatval/(1 - hatval) # Potential division by zero here #
plot(g, cook, xlim =3D c(0, max(g)), ylim =3D c(0, ymx),=20
main =3D main, xlab =3D "Leverage", ylab =3D "Cook's distance",=
=20
xaxt =3D "n", type =3D "n", ...)
...
All other values of 'which' seem to work fine. Sorry not to have checked =
this in the beta version,
Heather
Prof Brian Ripley <ripley at stats.ox.ac.uk> 12/06/05 04:10pm >>>
Curiously, I was just looking at that, since I believe the answer = should=20 be NaN, and some optimizing compilers/fast BLASes are not giving that. (There's an example in reg-test-3.R.) So I think we need to return NaN=20 when hat is within rounding error of 1. My take is that plot.lm should handle this: you will see most but not = all=20 cases have na.rm=3DTRUE in calculating ylim, but as Inf is theoretically impossible it has not been considered. Note that plot.lm does not use rstandard and so needs a separate fix. Thanks for the report
On Tue, 6 Dec 2005 Heather.Turner at warwick.ac.uk wrote:
Full_Name: Heather Turner Version: 2.2.0 OS: Windows XP Submission from: (NULL) (137.205.240.44) Standardized residuals as calculated by rstandard.lm, rstandard.glm and =
plot.lm
are Inf/NaN rather than zero when the un-standardized residuals are =
zero. This
causes plot.lm to break when calculating 'ylim' for any of the plots of
standardized residuals. Example:
"occupationalStatus" <-
structure(as.integer(c(50, 16, 12, 11, 2, 12, 0, 0, 19, 40, 35,
20, 8, 28, 6, 3, 26, 34, 65, 58, 12, 102, 19, =
14, 8,
18, 66, 110, 23, 162, 40, 32, 7, 11, 35, 40, =
25, 90,
21, 15, 11, 20, 88, 183, 46, 554, 158, 126, 6, =
8,
23,
64, 28, 230, 143, 91, 2, 3, 21, 32, 12, 177, =
71,
106)
), .Dim =3D as.integer(c(8, 8)), .Dimnames =3D
structure(list(origin =3D c("1", "2", "3", "4", "5", "6", =
"7",
"8"),
destination =3D c("1", "2", "3", "4", "5", =
"6", "7",
"8")), .Names =3D c("origin", "destination"))=
,
class =3D "table")
Diag <- as.factor(diag(1:8))
Rscore <- scale(as.numeric(row(occupationalStatus)), scale =3D FALSE)
Cscore <- scale(as.numeric(col(occupationalStatus)), scale =3D FALSE)
Uniform <- glm(Freq ~ origin + destination + Diag +
Rscore:Cscore, family =3D poisson, data =3D occupationalSta=
tus)
residuals(Uniform)[as.logical(diag(8))] #zero/near-zero rstandard(Uniform)[as.logical(diag(8))] #mostly Inf/NaN plot(Uniform) #breaks on qqnorm plot (or any 'which' > 1) This could be fixed by replacing standardized residuals with zero where =
the hat
value is one, e.g.
rstandard.glm <- function (model,
infl =3D lm.influence(model, do.coef =3D =
FALSE),
...) {
res <- infl$wt.res
hat <- infl$hat
ifelse(hat =3D=3D 1, 0, res/sqrt(summary(model)$dispersion * (1 -
infl$hat)))
}
etc.
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--=20 Brian D. Ripley, ripley at stats.ox.ac.uk=20 Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/=20 University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595