if(identical(Sys.getenv("NOT_CRAN"), "true")& .Machine$sizeof.pointer != 4){
  
  library(ctsem)
  library(testthat)
  set.seed(2)
  
  context("tipredcheck")
  
  test_that("simpleTIpredcheck", {
    Tpoints=10
    n.manifest=1
    n.TDpred=0
    n.TIpred=1
    n.latent=1
    n.subjects=50
    TI1 <- rnorm(n.subjects)
    gm<-ctModel(type='omx', Tpoints=Tpoints,n.latent=n.latent,
      n.TDpred=n.TDpred,n.manifest=n.manifest,
      MANIFESTVAR=diag(0.5,1),
      LAMBDA=diag(1,1),T0MEANS=100,
      DRIFT=matrix(c(-.3),nrow=1),
      DIFFUSION=matrix(c(2),1),
      T0VAR=diag(10,1))
    
    for(i in 1:n.subjects){
      gm$CINT[1,1] <- TI1[i]*5+rnorm(1,0,.6)
      ndat<-suppressMessages(ctGenerate(gm,n.subjects=1,burnin=10,logdtsd=.4))
      ndat <- cbind(ndat,TI1[i])
      ndat[,1] <- i
      if(i>1) tdat <- rbind(tdat,ndat) else tdat <- ndat
    }
    colnames(tdat)[4] <- 'TI1'
    
    tdat[2,'Y1'] <- NA
    tdat[tdat[,'id']==2,'TI1'] <- NA
    
    checkm<-suppressMessages(ctModel(type='stanct',Tpoints=Tpoints,
      MANIFESTVAR=diag(0.5,1),
      DRIFT=matrix(c(-.3),nrow=1),
      DIFFUSION=matrix(c(2),1),
      n.latent=n.latent,n.TDpred=n.TDpred,
      n.TIpred=n.TIpred,
      MANIFESTMEANS=matrix(0,nrow=n.manifest),
      CINT=matrix(c('cint1'),ncol=1),
      n.manifest=n.manifest,LAMBDA=diag(1)))
    
    # checkm$pars$indvarying <- FALSE
    
    checkm$pars[c(-1,-7) ,c('TI1_effect')] <- FALSE
    
    tfit1<-ctStanFit(tdat,checkm,chains=1,cores=2,optimize=TRUE,
      optimcontrol=list(is=TRUE,finishsamples=500),
      priors=TRUE,verbose=0)
    s1=summary(tfit1)
    
    expect_equivalent(s1$tipreds[2,'mean'],5,tolerance=.1)
    expect_equivalent(s1$popsd[2,'mean'],.6,tolerance=.2)
    
    tfit2<-ctStanFit(tdat,checkm,optimize=TRUE,cores=2,verbose=0,
      optimcontrol=list(is=FALSE),priors=TRUE)
    s2=summary(tfit2)
    
    expect_equivalent(s2$tipreds[2,'mean'],5,tolerance=.1)
    expect_equivalent(s2$popsd[2,'mean'],.6,tolerance=.2)
    
    tfit3<-suppressWarnings(ctStanFit(tdat,checkm,iter=300,chains=2,optimize=FALSE,
      control=list(adapt_delta=.8,max_treedepth=6),plot=FALSE))
    s3=summary(tfit3)
    
    expect_equivalent(s3$tipreds[2,'mean'],5,tolerance=.1)
    expect_equivalent(s3$popsd[2,'mean'],.6,tolerance=.2)
  })
}