facloaddensplot

<code>facloaddensplot</code> draws kernel smoothed density plots of the marginal
factor loadings posterior.

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

facloaddensplot function

<dl><dt>x</dt>
<dd>Object of class <code>'fsvdraws'</code>, usually resulting from a call
to <code>fsvsample</code>.</dd>
<dt>fsvsimobj</dt>
<dd>To indicate data generating values in case of simulated
data, pass an object of type <code>fsvsim</code> (usually the result of a
call to <code>fsvsim</code>).</dd>
<dt>rows</dt>
<dd>Number of rows per page.</dd>
<dt>thesecols</dt>
<dd>Which factor loadings columns should be plotted? Defaults to 1:r.</dd>
<dt>xlim</dt>
<dd>Vector of length two containing lower and upper bounds of the
horizontal axis. If <code>NULL</code>, these are automatically determined.</dd></dl>

Arguments

Density plots of factor loadings draws — facloaddensplot

<dl>

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


<dt>fsvsimobj</dt>
<dd>To indicate data generating values in case of simulated
data, pass an object of type <code>fsvsim</code> (usually the result of a
call to <code>fsvsim</code>).</dd>


<dt>rows</dt>
<dd>Number of rows per page.</dd>


<dt>thesecols</dt>
<dd>Which factor loadings columns should be plotted? Defaults to 1:r.</dd>


<dt>xlim</dt>
<dd>Vector of length two containing lower and upper bounds of the
horizontal axis. If <code>NULL</code>, these are automatically determined.</dd>

</dl>

facloaddensplot: Density plots of factor loadings draws

Description

Usage

Value

Arguments

See Also