voltimeplot

Object of class <code>'fsvdraws'</code>, usually resulting from a call
to <code><a rd-options="" href="/link/fsvsample?package=factorstochvol&version=0.8.1" data-mini-rdoc="factorstochvol::fsvsample">fsvsample</a></code>.

Index vector containing the time points to plot. Defaults
to <code>seq_len(nrow(x$y))</code>, i.e., all timepoints.

these

Where to position the <code>link{legend}</code>. 
If set to NULL, labels will be put directly next to the series.
Defaults to "topright".

legend

Additional parameters will be passed on to <code><a rd-options="" href="/link/ts.plot?package=factorstochvol&version=0.8.1" data-mini-rdoc="factorstochvol::ts.plot">ts.plot</a></code>.


<code>voltimeplot</code> plots the marginal volatilities over time, i.e. the
series-specific conditional standard deviations. If these haven't been
stored during sampling (because <code>runningstore</code> has been set too low),
<code>voltimeplot</code> throws a warning.


Markov chain Monte Carlo (MCMC) sampler for fully Bayesian
estimation of latent factor stochastic volatility models.
Sparsity can be achieved through the usage of Normal-Gamma priors
on the factor loading matrix.

Gregor Kastner

factorstochvol

Bayesian Estimation of (Sparse) Latent Factor Stochastic
Volatility Models

voltimeplot function

Object of class <code>'fsvdraws'</code>, usually resulting from a call
to <code><a rd-options='' href='fsvsample'>fsvsample</a></code>.

Additional parameters will be passed on to <code><a rd-options='' href='ts.plot'>ts.plot</a></code>.

voltimeplot: Plot series-specific volatilities over time.

Description

Usage

Arguments

Value

See Also