[R-sig-ME] Unacceptibly high autocorrelation in MCMCglmm

[Jarrod Hadfield]

HI,

It looks like the probit has underflowed/overflowed - you can check  
this by saving the latent variables and looking to see whether the  
range of the absolute values exceeds 7 (See Section 8.08 of  
CourseNotes).

This can happen with weak priors and (near) complete separation and/or  
with weak priors for effects that are heavily confounded.

I'm not sure how to proceed with underflow/overflow problems  
generally.  I could terminate the procedure, or I could truncate the  
latent variables at their overflow/underflow points. The latter is  
used by some WinBUGS users, but then WinBUGS handles the fact that the  
response is from a truncated normal not a normal - something which  
would be hard to program in MCMCglmm. Any thoughts would be useful.

Cheers,

Jarrod



Quoting Stuart Luppescu <slu at ccsr.uchicago.edu> on Fri, 16 Mar 2012  
17:38:15 -0500:

> Hello, I'm running this ordered category outcome model:
>
> glme5.very.len <- MCMCglmm(very.len.summative.o ~ 1 ,
>                    prior=list(R=list(V=1, fix=1), G=list(G1=list(V=1,
> nu=0), G2=list(V=1, nu=0), G3=list(V=1, nu=0), G4=list(V=1, nu=0) )),
>                    random = ~emplid + deptid + grade.f + subject.f ,
>                    family = "ordinal",
>                    nitt=300000,
>                    data = summative.ratings.prin.yr1.full)
>
> I ran it first with nitt=100000 but had very high autocorrelations and
> non-sensical variance components and fixed effects, so I increased nitt
> to 200000 and then to 300000 but got no change. Here's the summary
> output:
>
>  summary(glme5.very.len)
>
>  Iterations = 3001:299991
>  Thinning interval  = 10
>  Sample size  = 29700
>
>  DIC: -13239.32
>
>  G-structure:  ~emplid
>
>        post.mean  l-95% CI u-95% CI eff.samp
> emplid     405.3 1.493e-11     1106    7.909
>
>                ~deptid
>
>        post.mean  l-95% CI u-95% CI eff.samp
> deptid     131.8 1.118e-16    475.2    42.65
>
>                ~grade.f
>
>         post.mean  l-95% CI u-95% CI eff.samp
> grade.f    0.9143 1.405e-17    1.575    15784
>
>                ~subject.f
>
>           post.mean  l-95% CI u-95% CI eff.samp
> subject.f     1.633 1.951e-17    2.748    10101
>
>  R-structure:  ~units
>
>       post.mean l-95% CI u-95% CI eff.samp
> units         1        1        1        0
>
>  Location effects: very.len.summative.o ~ 1
>
>             post.mean l-95% CI u-95% CI eff.samp  pMCMC
> (Intercept)    29.007    2.091   54.969    2.381 <3e-05 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
>  Cutpoints:
>                                      post.mean l-95% CI u-95% CI eff.samp
> cutpoint.traitvery.len.summative.o.1     14.06   0.8102    27.38    9.382
> cutpoint.traitvery.len.summative.o.2     40.34   2.9611    76.04    2.694
>
> Here are some of the autocorrs:
>
>  autocorr(glme5.very.len$VCV)
> , , emplid
>
>            emplid    deptid    grade.f  subject.f units
> Lag 0   1.0000000 0.5860851 0.04668197 0.06081864   NaN
> Lag 10  0.9514313 0.6132116 0.04345287 0.05652945   NaN
> Lag 50  0.9459831 0.6259477 0.04881253 0.06093640   NaN
> Lag 100 0.9433509 0.6282599 0.04492884 0.06037288   NaN
> Lag 500 0.9267886 0.6373151 0.03873992 0.05371885   NaN
>
> , , deptid
>
>            emplid    deptid    grade.f  subject.f units
> Lag 0   0.5860851 1.0000000 0.03070680 0.03453008   NaN
> Lag 10  0.6137187 0.7579551 0.03233992 0.04139315   NaN
> Lag 50  0.6255810 0.7169468 0.02903334 0.03960446   NaN
> Lag 100 0.6269979 0.7029498 0.03244468 0.04857241   NaN
> Lag 500 0.6322900 0.6650247 0.04049514 0.04306019   NaN
>
> Is there a problem in my data or in the model?
>
> Thank you.
>
> --
> Stuart Luppescu -=- slu .at. ccsr.uchicago.edu
> University of Chicago -=- CCSR
> 才文と智奈美の父 -=-    Kernel 3.2.1-gentoo-r2
> Benjamin Lloyd-Hughes: Has anyone had any joy
>  getting the rgdal package to compile under
> <windows? Roger Bivand: The closest anyone has got
>  so far is Hisaji Ono, who used MSYS
>  (http://www.mingw.org/) to build PROJ.4 and GDAL
>  (GDAL depends on PROJ.4, PROJ.4 needs a PATH to
>  metadata files for projection and transformation),
>  and then hand-pasted the paths to the GDAL headers
>  and library into src/Makevars, running Rcmd
>
> _______________________________________________
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> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>



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