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/ =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- r-testers mailing list -- To (un)subscribe, send subscribe or unsubscribe (in the "body", not the subject !) To: r-testers-request@stat.math.ethz.ch =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-