Hi:
To test the situation below I am creating 2 datasets
.#Set working directory
setwd("C://Tina/USB_Backup_042213/Testing/CSV")
matrix=NULL
csvs <- paste("MVN", 1:2, ".csv", sep="")
for(i in 1:length(csvs)){
matrix[[i]] <- read.csv(file=csvs[i], header=T)
print(matrix[[i]])
}
So now I have read in 2 simulated datasets which look like
Y1 Y2
1 11 6
2 8 5
3 25 13
4 1 13
5 8 22
Y1 Y2
1 9 1
2 7 9
3 25 13
4 1 18
5 9 12
My next step is to run a multivariate logit normal model on these datasets
and automate this process for 300 such simulated datasets. Heres the model
statement:
model
{
for (j in 1 : Nf)
{
p1[j, 1:2 ] ~ dmnorm(gamma[1:2 ], T[1:2 ,1:2 ])
for (i in 1:2)
{
logit(p[j,i])<-p1[j,i]
Y[j,i] ~ dbin(p[j,i],n)
}}
I am trying to use the following code to run it in R2WinBUGS
bugs.output <- list()
for(i in 1:2){ # for 2 simulated datasets for
now
*Y <-(matrix[i])* * *
bugs.output[[i]] <- bugs(
data=list(Y=Y, Nf=5), # change for no of sites
inits=NULL,
model.file="M-LN_model_trial.txt",
parameters.to.save = c("p","rho","sigma2"),
n.chains=1, n.iter=12000, n.burnin=5000,
bugs.directory="C://Tina/USB_Backup_042213/winbugs14/WinBUGS14",
working.directory=NULL)}
Any suggestion would be helpful.
Thanks!
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