ctStanModel: Convert a frequentist (omx) ctsem model specification to...

In ctsem: Continuous Time Structural Equation Modelling

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)

ctsem documentation built on Sept. 11, 2024, 9:06 p.m.