ctdataupdate<-function(forcerecompile=FALSE){
message(paste0('Updating from ',(getwd()),', continue T / F?'))
continue <- readline()
if(continue){
set.seed(1)
Tpoints=10
n.manifest=2
n.TDpred=1
n.TIpred=3
n.latent=2
n.subjects=30
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,-.7,0,2),nrow=2),
TIPREDVAR=matrix(c(1,-.2,0, 0,1,0, 0,0,.5),nrow=3),
TDPREDVAR=matrix(0,nrow=n.TDpred*(Tpoints),ncol=n.TDpred*(Tpoints)),
TDPREDMEANS=matrix(round(exp(rnorm(n.TDpred*(Tpoints),-1.9,1)),0),
nrow=n.TDpred*(Tpoints)),
TDPREDEFFECT = matrix(c(1,-1),ncol=1),
LAMBDA=diag(1,2),
DRIFT=matrix(c(-.3,.2,0,-.2),nrow=2),
DIFFUSION=matrix(c(2,1,0,2),2),
CINT=matrix(c(0,0),nrow=2),
T0MEANS=matrix(10,ncol=1,nrow=2),
T0VAR=diag(1,2))
ctstantestdat<-ctGenerate(gm,n.subjects=n.subjects,burnin=3,logdtsd=.4,dtmean = .3)
ctstantestdat[2,'Y1'] <- NA
ctstantestdat[ctstantestdat[,'id']==2,'TI1'] <- NA
ctstantestdat[2,'TD1'] <- NA
save(ctstantestdat,file='.\\data\\ctstantestdat.rda')
## now in zzz.R
checkm<-ctModel(
type='stanct',
n.latent=2,n.TDpred=1,n.TIpred=1,n.manifest=2,
MANIFESTVAR=matrix(c('merror',0,0,'merror'),2,2),
MANIFESTMEANS=0,
DRIFT=c('dr1','dr12','dr21||||TI1','dr22'),
DIFFUSION=c('diff11',0,'diff21','diff22||||TI1'),
CINT=matrix(c('cint1||||TI1','cint2||||TI1'),ncol=1),
LAMBDA=diag(2),tipredDefault=FALSE)
ctstantestfit<-ctStanFit(ctstantestdat,checkm,cores=1,inits=0,
optimize = TRUE,optimcontrol=list(finishsamples=20,stochastic=T,tol=1e-5),priors=TRUE)
ctstantestfit <- ctStanGenerateFromFit(ctstantestfit,nsamples = 20,fullposterior = TRUE,cores=1)
save(ctstantestfit,file='.\\data\\ctstantestfit.rda')
paths <- sort(Sys.glob(c("data/ctstantestfit.rda","data/ctstantestdat.rda"))) #
tools::resaveRdaFiles(paths)
}
}
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