ctStanModel {ctsem} | R Documentation |
Convert a frequentist (omx) ctsem model specification to Bayesian (Stan).
Description
Convert a frequentist (omx) ctsem model specification to Bayesian (Stan).
Usage
ctStanModel(ctmodelobj, type = "stanct", tipredDefault = TRUE)
Arguments
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. |
Value
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
.
Examples
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)
[Package ctsem version 3.10.1 Index]