### Create Table of GEE variance values
### First run 3 programs: sim.pois.exchange.fix.ssc, sim.pois.indep.nofix.ssc, sim.preisser.ssc

mat1<-matrix(NA,9,5,dimnames=list(NULL,c("Vsim","Vm","Vs","Vmd","Va")))

nsim<-1000

### GEE Pois, Exchangeable, tau=0
### create output list called out
source("out.sim.pois.exchange.fix")


index<-rep(T,nsim)
if (!is.null(out$erri.d1)) index[out$erri.d1]<-F 

###number of converging simulated data sets
length(out$bd1[index])
mat1[1,1]<-var(out$bd1[index])
mat1[1,2]<-mean(out$vd1[index,1])
mat1[1,3]<-mean(out$vd1[index,2])
mat1[1,4]<-mean(out$vd1[index,3])
mat1[1,5]<-mean(out$vd1[index,4])

### GEE Pois, Exchangeable, tau=1/2

index<-rep(T,nsim)
if (!is.null(out$erri.d4)) index[out$erri.d4]<-F 

###number of converging simulated data sets
length(out$bd4[index])
mat1[2,1]<-var(out$bd4[index])
mat1[2,2]<-mean(out$vd4[index,1])
mat1[2,3]<-mean(out$vd4[index,2])
mat1[2,4]<-mean(out$vd4[index,3])
mat1[2,5]<-mean(out$vd4[index,4])


### GEE Pois, Independent, tau=0
source("out.sim.pois.indep.nofix")
out<-out.sim.pois.indep.nofix



index<-rep(T,nsim)
if (!is.null(out$erri.d1)) index[out$erri.d1]<-F 

###number of converging simulated data sets
length(out$bd1[index])
mat1[3,1]<-var(out$bd1[index])
mat1[3,2]<-mean(out$vd1[index,1])
mat1[3,3]<-mean(out$vd1[index,2])
mat1[3,4]<-mean(out$vd1[index,3])
mat1[3,5]<-mean(out$vd1[index,4])

### GEE Pois, Independent, tau=1/2

index<-rep(T,nsim)
if (!is.null(out$erri.d4)) index[out$erri.d4]<-F 

###number of converging simulated data sets
length(out$bd4[index])
mat1[4,1]<-var(out$bd4[index])
mat1[4,2]<-mean(out$vd4[index,1])
mat1[4,3]<-mean(out$vd4[index,2])
mat1[4,4]<-mean(out$vd4[index,3])
mat1[4,5]<-mean(out$vd4[index,4])



### Preisser data (GUIDE data) simulation results
source("out.sim.preisser")
out<-out.sim.preisser

index<-rep(T,nsim)
if (!is.null(out$erri2)) index[out$erri2]<-F 
###number of converging simulated data sets
length(out$b2[index])
mat1[5,1]<-var(out$b2[index])
mat1[5,2]<-mean(out$v2[index,1])
mat1[5,3]<-mean(out$v2[index,2])
mat1[5,4]<-mean(out$v2[index,3])
mat1[5,5]<-mean(out$v2[index,4])

index<-rep(T,nsim)
if (!is.null(out$erri3)) index[out$erri3]<-F 
###number of converging simulated data sets
length(out$b3[index])
mat1[6,1]<-var(out$b3[index])
mat1[6,2]<-mean(out$v3[index,1])
mat1[6,3]<-mean(out$v3[index,2])
mat1[6,4]<-mean(out$v3[index,3])
mat1[6,5]<-mean(out$v3[index,4])

index<-rep(T,nsim)
if (!is.null(out$erri4)) index[out$erri4]<-F 
###number of converging simulated data sets
length(out$b4[index])
mat1[7,1]<-var(out$b4[index])
mat1[7,2]<-mean(out$v4[index,1])
mat1[7,3]<-mean(out$v4[index,2])
mat1[7,4]<-mean(out$v4[index,3])
mat1[7,5]<-mean(out$v4[index,4])

index<-rep(T,nsim)
if (!is.null(out$erri5)) index[out$erri5]<-F 
###number of converging simulated data sets
length(out$b5[index])
mat1[8,1]<-var(out$b5[index])
mat1[8,2]<-mean(out$v5[index,1])
mat1[8,3]<-mean(out$v5[index,2])
mat1[8,4]<-mean(out$v5[index,3])
mat1[8,5]<-mean(out$v5[index,4])

index<-rep(T,nsim)
if (!is.null(out$erri6)) index[out$erri6]<-F 
###number of converging simulated data sets
length(out$b6[index])
mat1[9,1]<-var(out$b6[index])
mat1[9,2]<-mean(out$v6[index,1])
mat1[9,3]<-mean(out$v6[index,2])
mat1[9,4]<-mean(out$v6[index,3])
mat1[9,5]<-mean(out$v6[index,4])


latex.tab<-function(mat){
	ncol<-dim(mat)[2]
	nrow<-dim(mat)[1]
	data<-data.frame(mat[,1],rep("&",nrow),row.names=rep(" ",nrow))
	for (i in 2:ncol){
		if (i<ncol) data<-data.frame(data,mat[,i],rep("&",nrow))
		else data<-data.frame(data,mat[,i],rep("\\",nrow))
	}
	data
}


round(mat1[,2:5] - mat1[,1],digits=6)

mat1.approx<-round(mat1,digits=5)



latex.tab(mat1.approx)