[R-sig-ME] non-positive definite matrix

[Timothy_Handley at nps.gov]

Hello,

I'm trying to use lmer to fit a linear mixed effects model to some data.
Unfortunately, lmer fails, saying "Error in mer_finalize(ans) : Downdated
X'X is not positive definite." While this may be a problem with my setup,
I've looked over it several times, so I think this is more likely a result
of my data. A quick search of the internet suggests that sometimes, the
random errors in real data are such that the resulting matrices are
mathematically unacceptable.

My one thought is that I might be able to avoid this problem by using a
function which fits a model via iteration/optimization. Based on a very
rough understanding of lmer, from Bates's book, my impression is that
*linear* mixed models are fit via some matrix method (akin to vanilla
least-squares regression), while generalized mixed models are fit via
optimization (similar to glm). If this is true, then if I could  get glmer
to fit my lmm via optimization, then perhaps I could fit this model to my
data without needing to tweak the data.

I would greatly appreciate any thoughts or advice any of you might have on
this problem. Thanks,

Tim Handley
Fire Effects Monitor
Santa Monica Mountains National Recreation Area
401 W. Hillcrest Dr.
Thousand Oaks, CA 91360
805-370-2300 x2412