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Convert a frequentist (omx) ctsem model specification to Bayesian (Stan).
ctStanModel(ctmodelobj, type = "stanct")
ctsem model object of type 'omx' (default)
either 'stanct' for continuous time, or 'standt' for discrete time.
List object of class ctStanModel, with random effects specified for any intercept type parameters
(T0MEANS, MANIFESTMEANS, and or CINT), and time independent predictor effects for all parameters. Adjust these
after initial specification by directly editing the pars
subobject, so model$pars
.
# NOT RUN {
model <- ctModel(type='omx', Tpoints=50,
n.latent=2, n.manifest=1,
manifestNames='sunspots',
latentNames=c('ss_level', 'ss_velocity'),
LAMBDA=matrix(c( 1, 'ma1' ), nrow=1, ncol=2),
DRIFT=matrix(c(0, 1, 'a21', 'a22'), nrow=2, ncol=2, byrow=TRUE),
MANIFESTMEANS=matrix(c('m1'), nrow=1, ncol=1),
# MANIFESTVAR=matrix(0, nrow=1, ncol=1),
CINT=matrix(c(0, 0), nrow=2, ncol=1),
DIFFUSION=matrix(c(
0, 0,
0, "diffusion"), ncol=2, nrow=2, byrow=TRUE))
stanmodel=ctStanModel(model)
# }
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