[Rd] proposal: allowing alternative variance estimators in glm/lm

[ivo welch]

Dear Brian / Thomas:

May I suggest a "cheap" and amateurish solution, obviously without much
knowledge or intelligence about the subject?

As a non-statistician user of R, maybe a hook functionality at strategic
places could provide some flexibility without too much pain.   I think
replacing the standard output from summary.lm would be a bad idea (it
could easily create errors downstream, when idiots like myself ask "why
don't I get the s.e. that stata produces?  duh---you loaded
heteroskedasticity adjustment, but forgot about it).  But I think some
flexibility to add more information would be a very good thing. 

Hooks that can be set by functions (perhaps cascades) would allow third
parties to create additional statistics, that could survive future
changes to the functions themselves, without requiring a full object
paradigm.   For example, summary.lm could provide two hooks that allow
programmers to chain my own objects to either the ans$coefficients and
the ans object.  (I guess even one hook would do.)  Well-thought-out
hooks could also add to print methods, etc., without requiring complete
function rewrites, and would survive future changes in the real R code
itself.

>From the perspective of a first-time amateurish end-user, an invokation
of "library(lm.addnormalized)" could then magically always add a
normalized coefficient to the coefficient output.  An invokation of
"library(lm.addheteroskedasticity)" could magically always add
heteroskedasticity se's and T-stats.  And so on.


As I said, I don't know what I am talking about.  I am really a
non-statistician end-user, who is really a bit over his head with all of
this---I am using R not because it is sensible given my needs and
abilities, but because I am in awe by many of its capabilities ( and
because I enjoy Brian berating me while he offers me usually desparately
needed help ;-) ).

Regards,

/ivo