Convert a frequentist (omx) ctsem model specification to Bayesian (Stan).
Convert a frequentist (omx) ctsem model specification to Bayesian (Stan).
ctStanModel(ctmodelobj, type = "stanct", tipredDefault = TRUE)
ctmodelobj |
ctsem model object of type 'omx' (default) |
type |
either 'stanct' for continuous time, or 'standt' for discrete time. |
tipredDefault |
Logical. TRUE sets any parameters with unspecified time independent predictor effects to have effects estimated, FALSE fixes the effect to zero unless individually specified. |
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 .
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.