## Not run:
# Tpoints=50
# n.manifest=2
# n.TDpred=1
# n.TIpred=3
# n.latent=2
# n.subjects=5
# gm<-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(.5,0,0,-.5,0,0),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),
# TRAITVAR=t(chol(matrix(c(4,3,3,4),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))
#
# ctstantestdat<-ctGenerate(gm,n.subjects=n.subjects,burnin=30,
# wide=FALSE, simultdpredeffect = TRUE)
# save(ctstantestdat,file='.\\data\\ctstantestdat.rda')
# paths <- sort(Sys.glob(c("data/*.rda", "data/*.RData")))
# library(tools)
# resaveRdaFiles(paths)
# ## End(Not run)
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