## Not run:
# ### generator for ctstantestfit
# set.seed(2)
# Tpoints=50
# n.manifest=2
# n.TDpred=0
# n.TIpred=3
# n.latent=2
# n.subjects=3
#
# testm<-ctModel(type='omx',Tpoints=Tpoints,n.latent=n.latent,
# n.TDpred=n.TDpred,n.TIpred=n.TIpred,n.manifest=n.manifest,
# MANIFESTVAR=diag(0.5,2),
# TIPREDEFFECT=matrix(c(0,0,0,0,0,0),nrow=2),
# TIPREDVAR=matrix(c(1,-.2,0, 0,1,0, 0,0,.5),nrow=3),
# TDPREDEFFECT=matrix(c(.1,-.2),nrow=2),
# TDPREDVAR=matrix(0,nrow=n.TDpred*(Tpoints-1),ncol=n.TDpred*(Tpoints-1)),
# TDPREDMEANS=matrix(rnorm(n.TDpred*(Tpoints-1),0,1),nrow=n.TDpred*(Tpoints-1)),
# LAMBDA=diag(1,2),
# DRIFT=matrix(c(-.3,.2,-.1,-.2),nrow=2),
# DIFFUSION=matrix(c(.3,.1,0,.2),2),CINT=matrix(c(0,0),nrow=2),
# T0MEANS=matrix(0,ncol=1,nrow=2),
# T0VAR=diag(100,2))
# cd<-ctGenerate(testm,n.subjects=n.subjects,burnin=300,simultdpredeffect=TRUE,wide=FALSE)
#
# checkm<-ctModel(type='stanct',Tpoints=Tpoints,
# n.latent=n.latent,n.TDpred=n.TDpred,n.TIpred=n.TIpred,
# n.manifest=n.manifest,LAMBDA=diag(2))
#
# checkm$pars$indvarying[-1:-2] <- FALSE
#
# ctstantestfit<-ctStanFit(cd,checkm,iter=20,chains=1,initwithoptim=TRUE)
# save(ctstantestfit,file='.\\data\\ctstantestfit.rda')
# ## End(Not run)
Run the code above in your browser using DataLab