R Under development (unstable) (2024-09-18 r87177 ucrt) -- "Unsuffered Consequences"
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> # set.seed(123)
> # 
> # library(Qval)
> # library(ddpcr)
> # 
> # ## generate Q-matrix and data
> # K <- 5
> # I <- 20
> # IQ <- list(
> #   P0 = runif(I, 0.1, 0.3),
> #   P1 = runif(I, 0.7, 0.9)
> # )
> # 
> # QRR1 <- QRR2 <- 0
> # times <- 1
> # for(t in 1:times){
> #   quiet({
> #     Q <- sim.Q(K, I)
> #     data <- sim.data(Q = Q, N = 500, IQ = IQ, model = "GDINA", distribute = "horder")
> #     Y <- data$da
> #     
> #     ## simulate random mis-specifications
> #     MQ <- sim.MQ(Q, 0.1)
> #     
> #     CDM.obj <- CDM(data$dat, MQ)
> #     GDINA.obj <- CDM.obj$analysis.obj
> #     
> #     obj1 <- validation(data$dat, MQ, CDM.obj, method = "Hull", search.method = "ESA") 
> #     obj2 <- validation(data$dat, MQ, CDM.obj, method = "Hull", search.method = "PAA") 
> #   })
> #   
> #   QRR1 <- QRR1 + zQRR(Q, obj1$Q.sug)
> #   QRR2 <- QRR2 + zQRR(Q, obj2$Q.sug)
> #   cat(t, ": QRR.1 =", round(QRR1/t, 3), " QRR.2 =", round(QRR2/t, 3), "\n")
> # }
> # 
> # 
> # # {
> # #   Hull[is.nan(Hull)] <- 0
> # #   number.of.parameters <- c(0, npk[c(which(Hull>0)+1, K+1)])
> # #   fit.index <- c(0, criterion[c(which(Hull>0)+1, K)])
> # #   plot(number.of.parameters, fit.index, type = "o", main = "Hull plot")
> # # }
> 
> proc.time()
   user  system elapsed 
   0.10    0.04    0.14