print.shrinkTVPVAR

Nicer printing of shrinkTVPVAR objects

Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter vector autoregressive models with shrinkage priors. Details on the algorithms used are provided in
Cadonna et al. (2020) <doi:10.3390/econometrics8020020> and Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.

Peter Knaus

shrinkTVPVAR

Efficient Bayesian Inference for TVP-VAR-SV Models with
Shrinkage

print.shrinkTVPVAR function

<dl><dt>x</dt>
<dd>a <code>shrinkTVPVAR</code> object.</dd>
<dt>...</dt>
<dd>Currently ignored.</dd></dl>

Arguments

Peter Knaus <a href="/link/peter.knaus%40wu.ac.at?package=shrinkTVPVAR&version=0.1.1" data-mini-rdoc="shrinkTVPVAR::peter.knaus@wu.ac.at">peter.knaus@wu.ac.at</a>

Author

Nicer printing of shrinkTVPVAR objects — print.shrinkTVPVAR

<dl>

<dt>x</dt>
<dd>a <code>shrinkTVPVAR</code> object.</dd>


<dt>...</dt>
<dd>Currently ignored.</dd>

</dl>

Peter Knaus <a href='mailto:peter.knaus@wu.ac.at'>peter.knaus@wu.ac.at</a>

print.shrinkTVPVAR: Nicer printing of shrinkTVPVAR objects

Description

Usage

Value

Arguments

Author