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# pmeans.hcoef=function(x,burnin=trunc(.1*R),...){
pmeans.hcoef=function(x,burnin=trunc(.1*R))
{
#
# arrays of draws of coefs in hier models
# 3 dimensional arrays: unit x var x draw
#
X=x
if(mode(X) == "list") stop("list entered \n Possible Fixup: extract from list \n")
if(mode(X) !="numeric") stop("Requires numeric argument \n")
d=dim(X)
if(length(d) !=3) stop("Requires 3-dim array \n")
nunits=d[1]
nvar=d[2]
R=d[3]
if(R < 100) {cat("fewer than 100 draws submitted \n"); return(invisible())}
# posterior means for each var
# par(las=1)
pmeans=matrix(0,nrow=nunits,ncol=nvar)
for(i in 1:nunits) pmeans[i,]=apply(X[i,,(burnin+1):R],1,mean)
names=as.character(1:nvar)
attributes(pmeans)$class="hcoef.post"
for(i in 1:nvar) names[i]=paste("Posterior Means of Coef ",i,sep="")
return(pmeans)
}
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