[R] Failure to run mcsamp() in package arm
Michael Kubovy
kubovy at virginia.edu
Wed Mar 7 23:46:45 CET 2007
Andrew Robinson has gently chided me for not including more
information. So here goes:
R version 2.4.1 (2006-12-18)
powerpc-apple-darwin8.8.0
locale:
C
attached base packages:
[1] "stats" "graphics" "grDevices" "utils" "methods" "base"
other attached packages:
foreign car arm R2WinBUGS lme4
Matrix lattice
"0.8-18" "1.2-1" "1.0-13" "2.0-4" "0.9975-13"
"0.9975-11" "0.14-16"
MASS JGR iplots JavaGD rJava
"7.2-32" "1.4-15" "1.0-5" "0.3-5" "0.4-14"
On Mar 7, 2007, at 4:30 PM, Michael Kubovy wrote:
> More problems. If I run
> sim(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
> from the lmer() help page.
>
> I get the error
> Error in mvrnorm(n.sims, bhat[j, ], V.beta) :
> 'Sigma' is not positive definite
>
> On Mar 7, 2007, at 1:30 PM, Michael Kubovy wrote:
>
>> Dear r-helpers,
>>
>> I can run the examples on the mcsamp help page. For example:
>> ****************************************
>>> M1 <- lmer (y1 ~ x + (1|group))
>>> (M1.sim <- mcsamp (M1))
>> fit using lmer,
>> 3 chains, each with 1000 iterations (first 500 discarded)
>> n.sims = 1500 iterations saved
>> mean sd 2.5% 25% 50% 75% 97.5% Rhat
>> n.eff
>> beta.(Intercept) 0.1 0.7 -1.2 -0.3 0.1 0.5 1.4 1.0
>> 1500
>> beta.x 2.5 0.4 1.7 2.2 2.5 2.7 3.2 1.0
>> 1500
>> sigma.y 3.8 0.3 3.3 3.6 3.7 3.9 4.3
>> 1.0 61
>> sigma.grop.(In) 1.5 0.8 0.0 1.0 1.4 1.9 3.3
>> 1.4 12
>> eta.group.(Intercept)[1] 0.0 1.0 -2.1 -0.5 0.0 0.6 2.0 1.0
>> 1500
>> eta.group.(Intercept)[2] 1.0 1.1 -0.9 0.2 0.9 1.7 3.4
>> 1.0 59
>> eta.group.(Intercept)[3] -1.3 1.2 -4.0 -2.0 -1.3 -0.4 0.5
>> 1.0 66
>> eta.group.(Intercept)[4] 1.3 1.1 -0.6 0.4 1.1 2.0 3.7
>> 1.1 43
>> eta.group.(Intercept)[5] -0.7 1.0 -3.0 -1.4 -0.6 0.0 1.2 1.0
>> 120
>> eta.group.(Intercept)[6] 1.5 1.2 -0.3 0.6 1.4 2.2 4.0
>> 1.0 49
>> eta.group.(Intercept)[7] 0.3 1.0 -1.7 -0.3 0.1 0.8 2.5 1.0
>> 440
>> eta.group.(Intercept)[8] -1.6 1.2 -4.0 -2.4 -1.5 -0.6 0.3
>> 1.1 41
>> eta.group.(Intercept)[9] 0.4 1.0 -1.6 -0.2 0.2 0.9 2.7 1.0
>> 180
>> eta.group.(Intercept)[10] -1.0 1.1 -3.3 -1.6 -0.9 -0.2 0.8
>> 1.0 86
>>
>> For each parameter, n.eff is a crude measure of effective sample
>> size,
>> and Rhat is the potential scale reduction factor (at convergence,
>> Rhat=1).
>> ****************************************
>> But when I try to do this with my own data I get an error:
>> ****************************************
>>> display(e7.lmer2)
>> lmer(formula = baLO ~ I(baRatio - 0.985) + delta + (1 + I(baRatio -
>> 0.985) + delta | subject), data = e7)
>> coef.est coef.se
>> (Intercept) -0.19 0.06
>> I(baRatio - 0.985) -4.95 0.74
>> delta 0.41 0.06
>> Error terms:
>> Groups Name Std.Dev. Corr
>> subject (Intercept) 0.13
>> I(baRatio - 0.985) 2.57 0.45
>> delta 0.22 -0.12 -0.94
>> Residual 0.39
>> number of obs: 494, groups: subject, 13
>> deviance = 551.4
>>
>>> e7.sim <- mcsamp(e7.lmer2)
>> Error in as.bugs.array(sims, program = "lmer", n.iter = n.iter,
>> n.burnin = n.burnin, :
>> error in parameter sigma. in parameters.to.save
>> ****************************************
>> I would appreciate a pointer to what the problem might be.
>> _____________________________
>> Professor Michael Kubovy
>> University of Virginia
>> Department of Psychology
>> USPS: P.O.Box 400400 Charlottesville, VA 22904-4400
>> Parcels: Room 102 Gilmer Hall
>> McCormick Road Charlottesville, VA 22903
>> Office: B011 +1-434-982-4729
>> Lab: B019 +1-434-982-4751
>> Fax: +1-434-982-4766
>> WWW: http://www.people.virginia.edu/~mk9y/
>>
>> ______________________________________________
>> R-help at stat.math.ethz.ch 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.
>
> ______________________________________________
> R-help at stat.math.ethz.ch 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.
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