# your code goes here
n1 <- 200
rep = 10
result1 = matrix(NA, rep, 5)
result2 = matrix(NA, rep, 5)
result3 = matrix(NA, rep, 5)
result4 = matrix(NA, rep, 5)
total = 0
set.seed(888)

for (i in 1 : rep){
        mydata <- simulateData(popmodel3.5,sample.nobs=n1)
        fit1 <- cfa(mismodel1.5, data = mydata, std.lv = T)
        fit2 <- cfa(mismodel2.5, data = mydata, std.lv = T)
        fit3 <- cfa(truemodel3.5, data = mydata, std.lv = T)
        fit4 <- cfa(mismodel4.5, data = mydata, std.lv = T)
        fit5 <- cfa(mismodel5.5, data = mydata, std.lv = T)
        if(
                fit1@Fit@converged == 'TRUE' && 
                min(eigen(fit1@Model@GLIST$theta)$values) > 0 &&
                min(eigen(fit1@Model@GLIST$psi)$values) > 0 &&
                min(eigen(inspect(fit1,"cov.ov"))$values) > 0 &&
                fit2@Fit@converged == 'TRUE' &&
                min(eigen(fit2@Model@GLIST$theta)$values) > 0 &&
                min(eigen(fit2@Model@GLIST$psi)$values) > 0 &&
                min(eigen(inspect(fit2,"cov.ov"))$values) > 0 &&
                fit3@Fit@converged == 'TRUE' &&
                min(eigen(fit3@Model@GLIST$theta)$values) > 0 &&
                min(eigen(fit3@Model@GLIST$psi)$values) > 0 &&
                min(eigen(inspect(fit3,"cov.ov"))$values) > 0 &&        
                fit4@Fit@converged == 'TRUE' &&
                min(eigen(fit4@Model@GLIST$theta)$values) > 0 &&
                min(eigen(fit4@Model@GLIST$psi)$values) > 0 &&
                min(eigen(inspect(fit4,"cov.ov"))$values) > 0 &&  
                fit5@Fit@converged == 'TRUE' &&
                min(eigen(fit5@Model@GLIST$theta)$values) > 0 &&
                min(eigen(fit5@Model@GLIST$psi)$values) > 0 &&
                min(eigen(inspect(fit5,"cov.ov"))$values) > 0 ){
                for(n in 1 : 5){
                        z <- paste("fit", n, sep = "")
                        z <- fi
                        result1[i, n] <- fitmeasures(z, c("ecvi"))
                        result2[i, n] <- fitmeasures(z, c("aic"))
                        result3[i, n] <- fitmeasures(z, c("bic"))    
                        result4[i, n] <- fitmeasures(z, c("bic2")) 
                }
                
        }
        else{
                total = total + i
        }
}