On Tue, Feb 16, 2010 at 10:54 AM, Luisa Carvalheiro <lgcarvalhe...@gmail.com> wrote: > Dear Douglas, > > Thank you for your reply. > Just some extra info on the dataset: In my case Number of obs is 33, > and number of groups of factor(Farm_code) is 12. > This is the information on iterations I get: > > summary(lmer(round(SR_SUN)~Dist_NV + (1|factor(Farm_code)) , > family=poisson, verbose =TRUE)) > 0: 60.054531: 1.06363 2.14672 -0.000683051 > 1: 60.054531: 1.06363 2.14672 -0.000683051 > Error in asMethod(object) : matrix is not symmetric [1,2] > In addition: Warning message: > In mer_finalize(ans) : singular convergence (7)
> When I run a similar model (exp variable Dist_hives) the number of > iterations is 11: > summary(lmer(round(SR_SUN)~Dist_hives + (1|factor(Farm_code)) , > family=poisson, verbose =TRUE)) > 0: 61.745238: 0.984732 1.63769 0.000126484 > 1: 61.648229: 0.984731 1.63769 -2.08637e-05 > 2: 61.498777: 0.984598 1.63769 4.11867e-05 > 3: 47.960908: 0.381062 1.63585 6.77029e-05 > 4: 46.223789: 0.250732 1.66727 8.31854e-05 > 5: 46.222223: 0.250732 1.66727 6.97790e-05 > 6: 46.216710: 0.250730 1.66727 7.60560e-05 > 7: 46.168835: 0.230386 1.64883 9.16430e-05 > 8: 46.165955: 0.228062 1.65658 8.70694e-05 > 9: 46.165883: 0.228815 1.65737 8.63400e-05 > 10: 46.165883: 0.228772 1.65734 8.63698e-05 > 11: 46.165883: 0.228772 1.65734 8.63701e-05 > I am very confused with the fact that it runs with Dist_hives and not > with Dist_NV. Both variables are distance values, the first having no > obvious relation with the response variable and the second (Dist_NV) > seems to have a negative effect on SR_SUN. As you say, Dist_hives has very little relationship to the response variable. The two fixed-effects coefficients are the last two parameters in the iteration output (the first parameter is the standard deviation of the random effects). So the slope with respect to Dist_hives for the linear predictor is 0.0000863. Either you have very large magnitudes of Dist_hives or that variable does not have much predictive power. For the second (Dist_NV) variable, the optimization algorithm is not able to make progress from the starting estimates. This may be an indication that the problem is badly scaled. Are the values of Dist_NV very large? If so, you may want to change the unit (say from meters to kilometers) so the values are much smaller. It may also help to use a starting estimate for the standard deviation of the random effects derived from the other model. That is, include start = 0.22 in the call to lmer. > Does this information helps identifying the problem with my data/analysis? > > Thank you, > > Luisa > > > > > On Tue, Feb 16, 2010 at 5:35 PM, Douglas Bates <ba...@stat.wisc.edu> wrote: >> This is similar to another question on the list today. >> >> On Tue, Feb 16, 2010 at 4:39 AM, Luisa Carvalheiro >> <lgcarvalhe...@gmail.com> wrote: >>> Dear R users, >>> >>> I am having problems using package lme4. >>> >>> I am trying to analyse the effect of a continuous variable (Dist_NV) >>> on a count data response variable (SR_SUN) using Poisson error >>> distribution. However, when I run the model: >>> >>> summary(lmer((SR_SUN)~Dist_NV + (1|factor(Farm_code)) , >>> family=poisson, REML=FALSE)) >>> >>> 1 error message and 1 warning message show up: >>> >>> in asMethod(object) : matrix is not symmetric [1,2] >>> In addition: Warning message: >>> In mer_finalize(ans) : singular convergence (7) >> >> So the first thing to do is to include the optional argument verbose = >> TRUE in the call to lmer. (Also, REML = FALSE is ignored for >> Generalized Linear Mixed Models and can be omitted. although there is >> no harm in including it.) >> >> You need to know where the optimizer is taking the parameter values >> before you can decide why. >> >> P.S. Questions like this will probably be more readily answered on the >> R-SIG-Mixed-Models mailing list. >> >>> A model including Dist_NV together with other variables runs with no >>> problems. >>> What am I doing wrong? >>> >>> Thank you, >>> >>> Luisa >>> >>> >>> -- >>> Luisa Carvalheiro, PhD >>> Southern African Biodiversity Institute, Kirstenbosch Research Center, >>> Claremont >>> & University of Pretoria >>> Postal address - SAWC Pbag X3015 Hoedspruit 1380, South Africa >>> telephone - +27 (0) 790250944 >>> carvalhe...@sanbi.org >>> lgcarvalhe...@gmail.com >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> > > > > -- > Luisa Carvalheiro, PhD > Southern African Biodiversity Institute, Kirstenbosch Research Center, > Claremont > & University of Pretoria > Postal address - SAWC Pbag X3015 Hoedspruit 1380, South Africa > telephone - +27 (0) 790250944 > carvalhe...@sanbi.org > lgcarvalhe...@gmail.com > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
