get.acf<-function(maxlag,oldei,the.lags) {
  #standardize variable
  ei<-(oldei-mean(oldei))/sd(oldei)
  #initialize variables
  N.list<-length(ei)
  ACF.list<-1
  total.sum<-0
  total.count<-0
  #cycle through all desired lags
  for (i in 1:maxlag) {
      all.guys<-NULL
      full.list<-NULL
      #cycle through lag lists looking for desired lag
      for (j in 1:length(the.lags)) {
          cur.lag<-the.lags[[j]]
          #calculate numerator terms of Morans I
          first.ei<-ei[((1+j):(length(the.lags[[j]])+j))[the.lags[[j]]==i]]
          second.ei<-ei[(1:(length(the.lags[[j]])))[the.lags[[j]]==i]]
          cur.term<-first.ei*second.ei
          full.list<-c(full.list,cur.term)
          #determine which observations were used for this lag  
          cur.guys<-unique(c(((1+j):(length(the.lags[[j]])+j))[the.lags[[j]]==i],
                      (1:(length(the.lags[[j]])))[the.lags[[j]]==i]))
          all.guys<-unique(c(all.guys,cur.guys))
      }
  #average sum of squares of all observations used
  bottom<-sum(ei[all.guys]^2)/length(ei[all.guys])
  #average lagged sum of squares
  top<-sum(full.list)/length(full.list)    
  cur.ACF<-top/bottom
  cur.N<-length(full.list)
  ACF.list<-c(ACF.list,cur.ACF)
  N.list<-c(N.list,cur.N)
  }
  out.mat<-cbind(0:maxlag,ACF.list,N.list)
  colnames(out.mat)<-c('lag','ACF','N')
  out.mat
}