Eno <-
function(obs, posdim){
#===============================================================================
#
#  Enlarge the size of obs to 10 and move posdim to first position 
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# 
dimsvar=dim(obs)
enlobs=enlarge(obs,10)
outdim=c(dimsvar,array(1,dim=(10-length(dimsvar))))
posaperm=1:10
posaperm[posdim]=1
posaperm[1]=posdim
enlobs=aperm(enlobs,posaperm)
dimsaperm=outdim[posaperm]
#
#  Loop on all dimensions to compute effective number of observations 
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
enleno=array(dim=c(1,dimsaperm[2:10]))
for (j2 in 1:dimsaperm[2]){
  for (j3 in 1:dimsaperm[3]){
    for (j4 in 1:dimsaperm[4]){
      for (j5 in 1:dimsaperm[5]){
        for (j6 in 1:dimsaperm[6]){
          for (j7 in 1:dimsaperm[7]){
            for (j8 in 1:dimsaperm[8]){
              for (j9 in 1:dimsaperm[9]){
                for (j10 in 1:dimsaperm[10]){
                  tmp=enlobs[,j2,j3,j4,j5,j6,j7,j8,j9,j10]
                  if ( length(sort(tmp)) > 1 ) {
                    n=length(sort(tmp))
                    a=acf(tmp,lag.max=n-1,plot=FALSE,na.action=na.pass)$acf[2:n,1,1]
                    s=0
                    for ( k in 1:(n-1) ) {
                      s=s+(((n-k)/n)*a[k])
                    }
                    enleno[1,j2,j3,j4,j5,j6,j7,j8,j9,j10]=min(n/(1+(2*s)),n)
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}
#
#  Back to the original dimensions
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
dimsvar=dimsvar[-posdim]
effnumobs=array(dim=dimsvar)
effnumobs[]=aperm(enleno,posaperm)
#
#  Outputs
# ~~~~~~~~~
#
effnumobs
#
}