From maechler at stat.math.ethz.ch  Fri May  9 15:39:31 2003
From: maechler at stat.math.ethz.ch (Martin Maechler)
Date: Fri May  9 14:39:40 2003
Subject: [Rd] Tolerances in glm.control
In-Reply-To: <Pine.LNX.4.44.0305091202550.1818-100000@gannet.stats>
References: <Pine.LNX.4.44.0305091202550.1818-100000@gannet.stats>
Message-ID: <16059.41347.381931.398340@gargle.gargle.HOWL>

>>>>> "BDR" == Prof Brian Ripley <ripley@stats.ox.ac.uk>
>>>>>     on Fri, 9 May 2003 12:08:10 +0100 (BST) writes:

    BDR> I have tightened the tolerances in glm.control in
    BDR> R-devel (aka 1.8.0 Under Development) from epsilon =
    BDR> 1e-4 to 1e-8, and increases maxit from 10 to 25.

    BDR> Normally the effect is to do one more iteration and get
    BDR> more accurate results.  However, in cases of partial
    BDR> separation several more iterations will be done and it
    BDR> will be clearer from the results which parameters are
    BDR> converging and which are diverging (to +/-Inf).

    BDR> I have been meaning to do this for some time (the
    BDR> defaults seemed appropriate to computer speeds at the
    BDR> 1991 origin of glm in S3), but have only this time
    BDR> remembered at the beginning of a release cycle.

Very good!

Being on this topic:  What about 
enhancing  summary.glm() and changing print.summary.glm() quite
a bit such that

o   summary.glm() for back compatibility still computes the Wald tests
		  but also does all the "drop1" tests for each coefficient
and

o  print.summary.glm() would print these tests instead of the 
		       (too often misleading) Wald ones.

Related: How hard would it be to compute a ``Hauck-Donner diagnostic''
	 warning?
	 (If it's an open research problem then it's "too hard"
	  for R 1.8 :-)

Martin Maechler <maechler@stat.math.ethz.ch>	http://stat.ethz.ch/~maechler/
Seminar fuer Statistik, ETH-Zentrum  LEO C16	Leonhardstr. 27
ETH (Federal Inst. Technology)	8092 Zurich	SWITZERLAND
phone: x-41-1-632-3408		fax: ...-1228			<><


[Rd] Tolerances in glm.control
Martin Maechler