From ripley at stats.ox.ac.uk  Wed Dec 27 19:43:57 2006
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Wed, 27 Dec 2006 18:43:57 +0000 (GMT)
Subject: [Rd] proposal: allowing alternative variance estimators in
	glm/lm
In-Reply-To: <Pine.LNX.4.64.0612270934220.25209@homer24.u.washington.edu>
References: <Pine.LNX.4.64.0612270934220.25209@homer24.u.washington.edu>
Message-ID: <Pine.LNX.4.64.0612271834520.11551@gannet.stats.ox.ac.uk>

What concerns me about this is if people call the summary methods directly 
on objects not of the right class.  That used to be quite prevalent in R 
itself, but problems with residuals/weights mean it has now gone, I 
believe.

summary.lm and summary.glm are exported from stats, and this indicates 
that they were quite widely used (and a grep across CRAN suggests that 
they still are).

One fairly backwards-compatible option would seem to be to call the vcov 
generic only if the object inherits from [g]lm and had an earlier class.


On Wed, 27 Dec 2006, Thomas Lumley wrote:

>
> There has been recent discussion about alternatives to the model-based
> standard error estimators for lm. While some people like the sandwich
> estimator and others don't, it is clear that neither estimator dominates
> the other for any sane loss function.  It is also worth noting that the
> sandwich estimator is the default for t.test().
>
> I think it would be useful for models using other variance estimators to
> be able to inherit from lm and use summary.lm and predict.lm (and
> similarly for glm).  The main step in making this possible would be
> moving the variance-covariance matrix computation that is currently
> duplicated in summary.lm and predict.lm into vcov.lm, and then having
> summary.lm and predict.lm call vcov().
>
> This allows a fitting function (whether lm() or another function) to
> produce objects that inherit usefully from lm and glm but have other
> standard error estimators, by supplying a new vcov method for the class.
> The initial discusssion was about heteroscedasticity-consistent sandwich
> estimators, but from my point of view autocorrelation-consistent
> estimators and estimators that handle sampling weights are more
> interesting.
>
> OOP purists might point out that the relationship involved is not,
> strictly speaking, inheritance.  They would be quite right. However,
> unless someone wants to rewrite glm and lm for S4 classes I think that
> battle is lost.
>
>
>     -thomas
>
> Thomas Lumley			Assoc. Professor, Biostatistics
> tlumley at u.washington.edu	University of Washington, Seattle
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



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