R-alpha: solve and 1 by 1 matrices

Douglas Bates (bates@stat.wisc.edu)
Thu, 29 Aug 96 13:56 CDT


Message-Id: <m0uwCG6-0000TzC@franz.stat.wisc.edu>
Date: Thu, 29 Aug 96 13:56 CDT
From: Douglas Bates <bates@stat.wisc.edu>
To: R-testers <r-testers@stat.math.ethz.ch>
Subject: R-alpha: solve and 1 by 1 matrices

I first noticed this when trying to get summary(fm) where fm is a
linear regression model without an intercept term.  Apparently solve()
doesn't handle 1 by 1 matrices well.
 > solve(diag(2))
      [,1] [,2]
 [1,]    1    0
 [2,]    0    1
 > solve(diag(1))
 Error: exact singularity in qr.coef
 > foo <- diag(1)
 > is.array(foo)
 [1] TRUE
 > dim(foo)
 [1] 1 1
 > foo
      [,1]
 [1,]    1
 > solve(foo)
 Error: exact singularity in qr.coef

I always thought that inverting 1 by 1 non-zero matrices would be
reasonably straightforward :-)

I'll try to track this one down a bit more.

-- 
Douglas Bates                            bates@stat.wisc.edu
Statistics Department                    608/262-2598
University of Wisconsin - Madison        http://www.stat.wisc.edu/~bates/
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