[R-sig-ME] increasing nAGQ causes error

[Ben Bolker]

  This sounds worth digging into, but it's hard to dig
into without a reproducible example.  I don't get the
problem with the GLMM example in the lme4 package:

example(lmer)
update(gm1,nAGQ=8)
update(gm1,nAGQ=10)

etc.

  Can you post your data set, or a subset or simulated
data set that gives the same problem, somewhere?

  Ben Bolker

Grant T. Stokke wrote:
> Hello All,
> 
> I'm new to R and new to this mailing list, so I hope I've presented
> the proper info in this post.  I'm using GLMMs to model the selection
> of urban roosting locations by crows.  My dataset consists of 22
> cities, with each city containing 1000 unused locations and from 83
> to 2000 used locations.  I have three covariates for each used or
> unused location which I've standardized across all observations: %
> canopy (CANS), % impervious surfaces (IMPS), and nighttime light
> level (LTS).  Using the default setting nAGQ=1, my full model is
> fitted without error:
> 
>> CIL_CIL<-glmer(USED~1+CANS+IMPS+LTS+(1+CANS+IMPS+LTS|CITY),family=binomial,data=sitescale)
>>  CIL_CIL
> Generalized linear mixed model fit by the Laplace approximation 
> Formula: USED ~ 1 + CANS + IMPS + LTS + (1 + CANS + IMPS + LTS |
> CITY) Data: sitescale AIC   BIC logLik deviance 15122 15237  -7547
> 15094 Random effects: Groups Name        Variance   Std.Dev. Corr
>  CITY   (Intercept) 321.698184 17.93595 CANS          0.073271
> 0.27069  0.026 IMPS          0.661947  0.81360  0.080 -0.698 LTS
> 455.829122 21.35016 -0.988  0.031 -0.132 Number of obs: 27128,
> groups: CITY, 22
> 
> Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept)
> -16.21878    4.01227  -4.042 5.29e-05 *** CANS          0.07881
> 0.07162   1.100 0.271147 IMPS          0.63137    0.17750   3.557
> 0.000375 *** LTS          19.50827    4.78822   4.074 4.62e-05 *** 
> --- Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> 
> Correlation of Fixed Effects: (Intr) CANS   IMPS CANS  0.020
>  IMPS  0.074 -0.500 LTS  -0.989  0.025 -0.124
> 
> When I increase nAGQ to 8, however, I get the following error:
> 
>> CIL_CIL.nAGQ8<-glmer(USED~1+CANS+IMPS+LTS+(1+CANS+IMPS+LTS|CITY),family=binomial,data=sitescale,nAGQ=8)
>>  CIL_CIL.nAGQ8
> Error in asMethod(object) : matrix is not symmetric [1,2]
> 
> I get the same error message with other values for nAGQ (I tried nAGQ
> = 2, 3, 5, and 50).  Is there anything I can do to fit the model
> using nAGQ > 1 without error?  Thanks in advance for your help!
> 
> -Grant Stokke
> 
> 
>> sessionInfo()
> R version 2.9.0 (2009-04-17) i386-pc-mingw32
> 
> locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
> States.1252;LC_MONETARY=English_United
> States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
> 
> attached base packages: [1] stats     graphics  grDevices utils
> datasets  methods   base
> 
> other attached packages: [1] mgcv_1.5-5         lme4_0.999375-30
> Matrix_0.999375-26 lattice_0.17-22
> 
> loaded via a namespace (and not attached): [1] grid_2.9.0
> nlme_3.1-90 tools_2.9.0
>> CIL_CIL.nAGQ8
> Error in asMethod(object) : matrix is not symmetric [1,2]
>> traceback()
> 18: .Call(dense_to_symmetric, from, "U", TRUE) 17: asMethod(object) 
> 16: as(from, "symmetricMatrix") 15: .class1(object) 14: as(as(from,
> "symmetricMatrix"), "dMatrix") 13: .class1(object) 12: as(as(as(from,
> "symmetricMatrix"), "dMatrix"), "denseMatrix") 11: .class1(object) 
> 10: as(as(as(as(from, "symmetricMatrix"), "dMatrix"), "denseMatrix"),
>  "dpoMatrix") 9: asMethod(object) 8: as(sigma(object)^2 *
> chol2inv(object at RX, size = object at dims["p"]), "dpoMatrix") 7:
> vcov(object) 6: vcov(object) 5: summary(x) 4: summary(x) 3:
> printMer(object) 2: function (object) standardGeneric("show")(<S4
> object of class "mer">) 1: function (object) 
> standardGeneric("show")(<S4 object of class "mer">)
> 
> 
> 
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-- 
Ben Bolker
Associate professor, Biology Dep't, Univ. of Florida
bolker at ufl.edu / www.zoology.ufl.edu/bolker
GPG key: www.zoology.ufl.edu/bolker/benbolker-publickey.asc