print.fsvdraws

Pretty printing of an fsvsdraws object

Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models with interweaving <doi:10.1080/10618600.2017.1322091>. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix <doi:10.1016/j.jeconom.2018.11.007>.

Gregor Kastner

factorstochvol

Bayesian Estimation of (Sparse) Latent Factor Stochastic
Volatility Models

Darjus Hosszejni

Luis Gruber

print.fsvdraws function

<dl><dt>x</dt>
<dd>Object of class <code>'fsvdraws'</code>, usually resulting from a call
of <code>fsvsample</code>.</dd>
<dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Pretty printing of an fsvsdraws object — print.fsvdraws

<dl>

<dt>x</dt>
<dd>Object of class <code>'fsvdraws'</code>, usually resulting from a call
of <code>fsvsample</code>.</dd>


<dt>...</dt>
<dd>Ignored.</dd>

</dl>

print.fsvdraws: Pretty printing of an fsvsdraws object

Description

Usage

Value

Arguments