# load ozone-mortality coefficients
out1<-matrix(scan('d:/feb08/UNC/s890/nmmaps/out1.txt'),ncol=4,byrow=T)
m1<-1000*out1[,1]
v1<-(1000*out1[,2])^2
# remove NAs
regind<-regind[!is.na(v1),]
m1<-m1[!is.na(v1)]
v1<-v1[!is.na(v1)]
# apply tlnise - remember to load first
tln1<-tlnise(m1,v1,w=regind,intercept=F)
# 
# output "national" estimates
tln1$gamma
# output individual city posterior estimates and standard errors
tln1$theta
tln1$SDtheta


# load regions data and convert to indicator variables
regions<-scan('d:/feb08/UNC/s890/nmmaps/regions.txt')
regind<-matrix(0,ncol=7,nrow=108)
for(i in 1:108){
if(region[i]==1)regind[i,]<-c(1,0,0,0,0,0,0)
if(region[i]==2)regind[i,]<-c(0,1,0,0,0,0,0)
if(region[i]==3)regind[i,]<-c(0,0,1,0,0,0,0)
if(region[i]==5)regind[i,]<-c(0,0,0,1,0,0,0)
if(region[i]==6)regind[i,]<-c(0,0,0,0,1,0,0)
if(region[i]==7)regind[i,]<-c(0,0,0,0,0,1,0)
if(region[i]==8)regind[i,]<-c(0,0,0,0,0,0,1)
}
# load ozone-mortality coefficients
out1<-matrix(scan('d:/feb08/UNC/s890/nmmaps/out1.txt'),ncol=4,byrow=T)
m1<-1000*out1[,1]
v1<-(1000*out1[,2])^2
# remove NAs
regind<-regind[!is.na(v1),]
m1<-m1[!is.na(v1)]
v1<-v1[!is.na(v1)]
# apply tlnise - remember to load first
tln1<-tlnise(m1,v1,w=regind,intercept=F)
# 
# output "national" estimates
tln1$gamma
# output individual city posterior estimates and standard errors
tln1$theta
tln1$SDtheta