c1.strs=function(data,y,g,m,ni,Ni){
  data=as.name(data); Ni=Ni; y=y; m=m; ni=ni; n=sum(ni)
  N=sum(Ni); fpci=(1-ni/Ni); ybari=tapply(y,g,mean,na.rm=T)
  s2ci=tapply(y,g,fun=sum((y-ybari*m)^2)/(n-1),na.rm=T)
  plot(m,y,main=data)
  mbari=tapply(m,g,mean,na.rm=T)
  M=sum(Ni*mbari)
  ybarc=(Ni*ybari)/sum(Ni*mbari)
  est=ybarc
  vhat=(1/M)*sum(Ni^2*fpci*(s2ci/ni))
  bound=2*sqrt(vhat)
  lower=est-bound; upper=est+bound
  cat("","\n","Results from 1-stage Cluster StRS sample: Data =",data,"\n","\n",
  "N =",N,"Ni =",Ni,"\n","n =",n,"ni =",ni,"\n",
"FPC =",fpc,"\n","Estimate of",param,"=",est,"\n",
"Vhat(", param,") =",vhat,"\n","Bound =",bound,"\n","Lower Bound =",lower,
"Upper Bound =",upper,"\n","")
  results=list(est=est,data=data,n=n,N=N,fpc=fpc,vhat=vhat,bound=bound,lower=lower,upper=upper)
}

# to use the function with its call:
# c1.strs(data,y,g,m,ni,Ni)

# data: name of dataset, in quotes
# y: numeric vector; the total of all observations in the ith cluster
# g: stratum vector
# m: cluster elements
# ni: stratum sample sizes (vector)
# Ni: stratum population sizes (vector)