How to compute mean of each variables of a list in R ?

#1
The following is a function of simulating data from simple linear regression and calculating non-coverage probability of each parameters .

Code:
simfun <- function(n,b0,b1,sig){
     x <- runif(n)
     y <- b0+b1*x+ rnorm(n,0,sig)
     data <- data.frame(y=y,x=x)
 }

noncoverage <- function(n,b0,b1,sig){

          dat <- simfun(n,b0,b1,sig)
          fit <- lm(y~x,data=dat)

          res=summary(fit)
         estim = coefficients(res)[,1]
         se=  coefficients(res)[,2]

         ci1 = estim[1] + qnorm(c(.025,.975))*se[1]
         nc1 = ifelse((ci1[1]<b0 & ci1[2]>b0),0,1)

       ci2 = estim[2] + qnorm(c(.025,.975))*se[2]
       nc2 = ifelse((ci2[1]<b1 & ci2[2]>b1),0,1)
       nc = data.frame(nc1=nc1,nc2=nc2)
}

set.seed(36)
com=replicate(4,noncoverage(200,1,2,.5))
and the output is :

Code:
> com
, , 1

  nc1 nc2
1 0   0  

, , 2

  nc1 nc2
1 1   0  

, , 3

  nc1 nc2
1 0   0  

, , 4

  nc1 nc2
1 0   0
I want to compute the mean of each variable ("nc1","nc2") in all replicates, that is mean of nc1 will be mean(c(0,1,0,0)) and mean of nc2 will be mean(c(0,0,0,0)) .

How can I compute the mean by R command ?

Many thanks! Regards.