Those errors indicate that the iterative step in the optimization of the
parameter estimates failed because of numerical singularities.  It would
help if you could post the results of

str(data)

Often these problems are indicative of trying to fit models that cannot be
supported by the data.


On Fri, Jan 4, 2013 at 3:40 PM, leanne heisler <leanneheisler@hotmail.com>wrote:

>
> Hi All,
> I am running a generalized linear mixed effects model with lme4 and am
> getting an error I have not been able to decipher. I was hoping for some
> guidance. I am using the following code:
>
> >
> glmer(DM~PREC+(1|NEST)+(1|NG)+(1|LONG),data=data,family=poisson,verbose=TRUE)
>  0: 6107.8287: 1.34084 1.29515 0.532795 3.23218 -0.00145626
>  1: 6107.8287: 1.34084 1.29515 0.532795 3.23218 -0.00145626
> Error in mer_finalize(ans) : Downdated X'X is not positive definite, 1.
> In addition: Warning messages:
> 1: In mer_finalize(ans) :
>  Cholmod warning 'not positive definite' at
> file:../Cholesky/t_cholmod_rowfac.c, line 431
> 2: In mer_finalize(ans) :
>  Cholmod warning 'not positive definite' at
> file:../Cholesky/t_cholmod_rowfac.c, line 431
> All fixed and random effects are continuous variables (DM is counts of
> deer mice) except for the random effect 'NEST', which is categorical. The
> model runs fine when the random effects NEST and LONG are removed.
>
> I feel I am doing something wrong here and would greatly appreciate any
> help from this mailing list.
>
> Thank you in advance.
> ---------------
>  Leanne Heisler
>  Graduate Student
>  Department of Biology
>  University of Regina
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>

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