Extract values from replicate functions

I am relatively new to R and am doing a MCMC simulation using R2OpenBUGS. My model works and I trying to do multiple iterations efficiently. This is my code for the multiple iterations.

mcmc.s=function(n1,m1,k1,al1,be1,R.x,n2,m2,k2,al2,be2,R.y) 
{
  tq.x=replicate(n1, aa(k1,al1,be1)) #produces data
  tq.y=replicate(n2, aa(k2,al2,be2)) #produces data

  x=pfF(n1,m1,k1,tq.x) #extracts samples from data
  y=pfF(n2,m2,k2,tq.y) #extracts samples from data

  x=c(x) #Need data inputed as a list
  y=c(y) #Need data inputed as a list

  datatemp<- list( "x","y","R.x","k1","m1","R.y","k2","m2") #these are just my inputs
  aaa<-rgamma(1, shape=4.5,rate=52) #prior
  bbb<-rgamma(1, shape=4.5,rate=52) #prior
  ccc<-rgamma(1, shape=20.5,rate=3.5) #prior

  initstemp<-function(){list(a=aaa,b=bbb,c=ccc)} #assigns priors to parameters in model
  bugstemp = bugs(data=datatemp,inits=initstemp,parameters.to.save=c("a","b","c"),n.iter= 50000, model.file=mtemp,
                  n.chains=3, n.burnin=40000,n.thin=1,codaPkg =F, debug=F)
  out<-bugstemp$summary
  acalc<-out["a","mean"];bcalc<-out["b","mean"];ccalc<-out["c","mean"] #line not necessary
  return(out)
}

iter=2
out=replicate(iter,mcmc.s(n1,m1,k1,al1,be1,R.x,n2,m2,k2,al2,be2,R.y))
out

The results look like:

, , 1

                mean         sd        2.5%      25%       50%      75%      97.5%     Rhat n.eff
a         0.07904428 0.03935658  0.02335975  0.05045  0.072255  0.10020  0.1738025 1.001631  2900
b         0.03557510 0.01966588  0.00946790  0.02168  0.031765  0.04493  0.0842925 1.001946  2000
c         7.05248063 2.62808107  3.24794998  5.19200  6.603000  8.43600 13.3402499 1.001574  5600
deviance 61.80275800 2.58984760 58.86000000 59.93000 61.130000 62.98000 68.6200000 1.006417   720

, , 2

               mean         sd        2.5%     25%      50%     75%     97.5%     Rhat n.eff
a         0.1992745 0.08962024  0.06359975  0.1340  0.18575  0.2506  0.413400 1.002039  1800
b         0.1648684 0.07519227  0.05357925  0.1103  0.15280  0.2070  0.341905 1.001840  2200
c         7.2121513 1.92005357  3.90300000  5.8610  7.05700  8.4000 11.320250 1.001200  8000
deviance 47.8683650 2.54986184 44.99000000 46.0300 47.22000 48.9900 54.530000 1.001291  5800

Is there a way to extract the means for the parameters a,b, and c? I thought about using a for loop in the simulation function like:

acalc<-numeric(length=iter)
bcalc<-numeric(length=iter)
ccalc<-numeric(length=iter)
for (i in 1:iter){acalc[i]<-out["a","mean"];bcalc[i]<-out["b","mean"];ccalc[i]<-out["c","mean"]}

But this does not seem to work. Any ideas on how I could extract this information would be extremely helpful. Thanks!