summary.ctStanFit

Summarise a ctStanFit object that was fit using <code>ctStanFit</code>.

Hierarchical continuous (and discrete) time state space modelling, for linear
and nonlinear systems measured by continuous variables, with limited support for
binary data. The subject specific dynamic system is modelled as a stochastic
differential equation (SDE) or difference equation, measurement models are typically multivariate normal factor models.
Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default.
Nonlinearities, (state dependent parameters) and random effects on all parameters
are possible, using either max likelihood / max a posteriori optimization
(with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling.
See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf>
for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian
linear SDE approach,
see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>.
Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> .
Stan based functions are not available on 32 bit Windows systems at present.
<https://cdriver.netlify.app/> contains some tutorial blog posts.

Charles Driver

ctsem

Continuous Time Structural Equation Modelling

Manuel Voelkle

Han Oud

Trustees of Columbia University 

summary.ctStanFit function

<dl><dt>object</dt>
<dd>fit object from <code>ctStanFit</code>, of class ctStanFit.</dd>
<dt>timeinterval</dt>
<dd>positive numeric indicating time interval to use for discrete time parameter calculations
reported in summary.</dd>
<dt>digits</dt>
<dd>integer denoting number of digits to report.</dd>
<dt>parmatrices</dt>
<dd>if TRUE, also return additional parameter matrices -- can be slow to compute
for large models with many samples.</dd>
<dt>priorcheck</dt>
<dd>Whether or not to use <code>ctsem:::priorchecking</code> to compare posterior mean and sd to prior mean and sd.</dd>
<dt>residualcov</dt>
<dd>Whether or not to show standardised residual covariance. Takes a little longer to compute.</dd>
<dt>...</dt>
<dd>Additional arguments to pass to <code>ctsem:::priorcheckreport</code>, such as <code>meanlim</code>, or <code>sdlim</code>.</dd></dl>

Arguments

summary.ctStanFit — summary.ctStanFit

<dl>

<dt>object</dt>
<dd>fit object from <code>ctStanFit</code>, of class ctStanFit.</dd>


<dt>timeinterval</dt>
<dd>positive numeric indicating time interval to use for discrete time parameter calculations
reported in summary.</dd>


<dt>digits</dt>
<dd>integer denoting number of digits to report.</dd>


<dt>parmatrices</dt>
<dd>if TRUE, also return additional parameter matrices -- can be slow to compute
for large models with many samples.</dd>


<dt>priorcheck</dt>
<dd>Whether or not to use <code>ctsem:::priorchecking</code> to compare posterior mean and sd to prior mean and sd.</dd>


<dt>residualcov</dt>
<dd>Whether or not to show standardised residual covariance. Takes a little longer to compute.</dd>


<dt>...</dt>
<dd>Additional arguments to pass to <code>ctsem:::priorcheckreport</code>, such as <code>meanlim</code>, or <code>sdlim</code>.</dd>

</dl>

summary.ctStanFit: summary.ctStanFit

Description

Usage

Value

Arguments

Examples