[Rd] glm gives incorrect results for zero-weight cases (PR#780)
Peter Dalgaard BSA
20 Dec 2000 13:37:55 +0100
> The reason is obvious: glm.fit only ever updates eta[good], and
> zero-weight values are not `good'. So eta[weights == 0] is stuck at the
> initial values.
> There are two possible fixes:
> 1) Update eta after the final fit, and then mu. Out of range values
> could then be NA (although it looks like predict.glm does not check).
> 2) Update all eta and hence mu values during the iterations. This will
> apply the constraints on eta/mu at zero-weight points too, and so might
> be different.
> I am inclined to think that 2) is right, and that adding points with zero
> weight to the fit is not the same as omitting them.
Just for clarification: This applies only to cases where the
parametrization is non-canonical, e.g. additive models with Poisson
response, right? And essentially the issue is that if you have a model
like lambda = a + b x and you put in a zero-weight observation with x
= 0, then that should effectively constrain a to be positive. That
does make quite good sense, yes.
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (email@example.com) FAX: (+45) 35327907
r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !) To: firstname.lastname@example.org