[Rd] proposal: allowing alternative variance estimators in glm/lm
Prof Brian Ripley
ripley at stats.ox.ac.uk
Wed Dec 27 19:43:57 CET 2006
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
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
> 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 Lumley Assoc. Professor, Biostatistics
> tlumley at u.washington.edu University of Washington, Seattle
> R-devel at r-project.org mailing list
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
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