get_default_fast_sv

get_default_general_sv

default_fast_sv

These functions define meaningful expert settings for
argument <code>expert</code> of <code>svsample</code> and its derivatives.
The result of <code>get_default_fast_sv</code> should be provided as
<code>expert$fast_sv</code> and <code>get_default_general_sv</code> as <code>expert$general_sv</code>
when relevant.

datasets

Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models with and without asymmetry (leverage) via Markov chain Monte Carlo (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Hosszejni and Kastner (2021) <doi:10.18637/jss.v100.i12> and Kastner (2016) <doi:10.18637/jss.v069.i05> and the package examples.

Darjus Hosszejni

stochvol

Efficient Bayesian Inference for Stochastic Volatility (SV)
Models

Gregor Kastner

get_default_fast_sv function

An object of class <code>list</code> of length 11.

Format

<dl><dt>priorspec</dt>
<dd>a <code>priorspec</code> object created by
<code>specify_priors</code></dd></dl>

Arguments

Default Values for the Expert Settings — get_default_fast_sv

<dl>

<dt>priorspec</dt>
<dd>a <code>priorspec</code> object created by
<code>specify_priors</code></dd>

</dl>

get_default_fast_sv: Default Values for the Expert Settings

Description

Usage

Format

Arguments

See Also