[R-sig-ME] problems fitting GLMM poisson with cross random effects in lme4 and glmmADMB

[Douglas Bates]

On Wed, Oct 31, 2012 at 12:00 PM, Pablo Inchausti
<pablo.inchausti.f at gmail.com> wrote:
> Dear all,
> I am experiencing problems when trying to fit the following GLMM with
> library lme4:
> m5=with(DF3,lmer(n.spp~log(hs.arrastre+1)+zona+prof+SSTA+zona*log(hs.arrastre+1)+zona*SSTA+zona*prof+
> (1|año) +(1|grado),weight=n.lances,family="poisson"))
>
> The response variable are counts (number of species), and there are four
> explanatory variables with fixed effects: three continuous variables (SSTA,
> arrastre, prof) and one is a three-level factor (zona). There are two
> crossed (uncorrelated random effects): (1|año) with año having 24 levels;
> the other random effect (1|grado) has by coincidence also 24 levels. The DF
> has 419 rows and no missing values.
> The numbers of cases for each of the random effects are unbalanced but not
> zero:
>> with(DF2, table(año))
> 1984 1985 1987 1988 1989 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
> 2001 2002 2003 2005 2006 2007 2008 2009 2010
>    3       4       3       29    12     23      8        8      40   31
>   9      12   12         6     14   32       7      8       28      31
> 35     26    26     12
>> with(DF2, table(grado))
> 333 342 343 344 345 352 353 354 355 356 363 364 365 366 374 375 376 385 386
> 387 395 396 397 398
>   7    35    22  18    9    22   31    25  18  17    28   32  10     6
> 22  26   11   13   18  13      9     9   12   6
>> with(DF2, table(grado, año)) is very sparse, which is why I am trying to
> fit uncorrelated random effects.
>
> I have used the very same dataset, with the same model structure) for other
> analyses with response variables having Gaussian distribution and have had
> no problems at all.
>
> I invariably obtain the error message:
> 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 432
> 2: In mer_finalize(ans) :
>   Cholmod warning 'not positive definite' at
> file:../Cholesky/t_cholmod_rowfac.c, line 432

> I have absolutely no idea how to interpret this message or resolve the
> error.

The error messages are coming from the sparse matrix library CHOLMOD.
One of the disadvantages of adopting such code in the Matrix package
for R is that it wants to provide its own error messages and without
considerable effort at rewriting it, which would need to be repeated
every time a new version is released, these messages show up as R
error messages.

The best thing to do is to trace the progress of the iterations in the
optimization of the parameter estimates.  You will likely find that
the fixed-effects parameters or the random effects are heading to
extreme values.

> After trying to fit the same model with library glmmAMDB, I obtain another
> (equally cryptical) error message:
> Error in II[, ii] = II[, ii] + REmat$codes[[i]] :
>   number of items to replace is not a multiple of replacement length
> In addition: Warning messages:
> 1: In glmmadmb(n.spp ~ log(hs.arrastre + 1) + zona + prof + SSTA +  :
>   NAs removed in constructing fixed-effect model frame: you should probably
> remove them manually, e.g. with na.omit()
> 2: In II[, ii] + REmat$codes[[i]] :
>   longer object length is not a multiple of shorter object length:
>
> I have tried many of the control options of either library (i.e. changing
> the # of iterations, of evaluations, etc) but the error messages remain
> unchanged.
>
> I would really appreciate if any of you could possible spare some minutes
> and suggest some alternative.
> Many thanks in advance,
> Cheers
>
>         [[alternative HTML version deleted]]
>
>
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