estimating error in function pgenlogis about sirt HOT 7 CLOSED

P_PGenlogis <- function( par, Theta, ncat){
  a <- par[1]
  b <- par[2]
  talpha1 <- par[3]
  talpha2 <- par[4]
  TP <- nrow(Theta)
  P <- matrix( NA, nrow=TP, ncol=ncat)
  P[,2] <- sirt::pgenlogis((a*(Theta[,1]- b)), alpha1=(exp(2*talpha1)-1)/(exp(2*talpha1)+1), alpha2=(exp(2*talpha2)-1)/(exp(2*talpha2)+1))
  P[,1] <- 1 - P[,2]
  return(P)
}

par <- c("a" = 1, "b" = 0, "talpha1" = 0, "talpha2" = 0)
item_1PGenlogis <- xxirt_createDiscItem( name = "1PGenlogis" , par = par, est = c(FALSE,TRUE,TRUE,TRUE), P = P_PGenlogis)
item_2PGenlogis <- xxirt_createDiscItem( name = "2PGenlogis" , par = par, est = c(TRUE,TRUE,TRUE,TRUE), P = P_PGenlogis)
customItems <- list(item_1PGenlogis, item_2PGenlogis)


mod.2PGenlogis.estimate <- function(dat, j){
  itemtype = rep( "2PGenlogis", j)
  partable = xxirt_createParTable(dat, itemtype = itemtype, customItems = customItems)
  parindex1 <- partable[ partable$parname=="talpha1","parindex"]
  parindex2 <- partable[ partable$parname=="talpha2","parindex"]
  lambda <- 1
  penalty_fun_item <- function(x){
    val <- (sum(sapply(x[parindex1], "-", x[parindex1])^2) + sum(sapply(x[parindex2], "-", x[parindex2])^2)) * lambda
    return(val)
  }
  smod2.2PGenlogis <- xxirt( dat=dat, Theta=Theta, partable=partable, maxit=3000, customItems=customItems, customTheta=customTheta, conv = 0.001, penalty_fun_item=penalty_fun_item, verbose = F)
  return(smod2.2PGenlogis)
}

Theta <- matrix( seq(-6,6,len=61) , ncol=1 )
P_Theta1 <- function( par , Theta , G){
  mu <- par[1]
  sigma <- max( par[2] , .01 )
  TP <- nrow(Theta)
  pi_Theta <- matrix( 0 , nrow=TP , ncol=G)
  pi1 <- dnorm( Theta[,1] , mean = mu , sd = sigma )
  pi1 <- pi1 / sum(pi1)
  pi_Theta[,1] <- pi1
  return(pi_Theta)
}

par_Theta <- c( "mu"=0, "sigma" = 1 )  
customTheta  <- xxirt_createThetaDistribution( par=par_Theta , est=c(F,T), P=P_Theta1 )

set.seed(2)
mod.2PGenlogis <- mod.2PGenlogis.estimate(dat = dat, j = 20)

mod.2PGenlogis.estimate <- function(dat, j){
  itemtype = rep( "2PGenlogis", j)
  partable = xxirt_createParTable(dat, itemtype = itemtype, customItems = customItems)
  smod1.2PGenlogis <- xxirt( dat=dat, Theta=Theta, partable=partable, maxit=10000, customItems=customItems, customTheta=customTheta, conv = 0.001, verbose = T)
  return(smod1.2PGenlogis)
}

alpha1=(exp(2*talpha1)-1)/(exp(2*talpha1)+1), alpha2=(exp(2*talpha2)-1)/(exp(2*talpha2)+1)

partable = xxirt_createParTable(dat, itemtype = itemtype, customItems = customItems)
parindex1 <- partable[ partable$parname=="talpha1","parindex"]
parindex2 <- partable[ partable$parname=="talpha2","parindex"]
lambda <- 1
penalty_fun_item <- function(x){
   val <- (sum(sapply(x[parindex1], "-", x[parindex1])^2) + sum(sapply(x[parindex2], "-", x[parindex2])^2)) * lambda
   return(val)
  }