sv_prior

This function computes the logarithm of the prior density for 
stochastic volatility models without leverage (symmetric stochastic volatility models):
mu~N(mu_0,sigma_0^2), (phi+1)/2~Beta(a_0,b_0), sigma_eta^2~IG(n_0/2,S_0/2)

The efficient Markov chain Monte Carlo estimation of stochastic volatility models with and without leverage (asymmetric and symmetric stochastic volatility models). Further, it computes the logarithm of the likelihood given parameters using particle filters.

Yasuhiro Omori

Stochastic Volatility Models with or without Leverage

Ryuji Hashimoto

sv_prior function

<dl> <dt>Theta_star</dt>
<dd>a vector of parameters to evaluate the prior density: Theta_star = c(mu, phi, sigma_eta)</dd> <dt>vHyper</dt>
<dd>a vector of hyper-parameters to evaluate the prior density: vHyper = c(mu_0, sigma_0, a_0, b_0, n_0, S_0)</dd></dl>

Arguments

Author

Compute the logarithm of the prior density for the stochastic volatility models without leverage — sv_prior

<dl>

 <dt>Theta_star</dt>
<dd>a vector of parameters to evaluate the prior density: Theta_star = c(mu, phi, sigma_eta)</dd>

 <dt>vHyper</dt>
<dd>a vector of hyper-parameters to evaluate the prior density: vHyper = c(mu_0, sigma_0, a_0, b_0, n_0, S_0)</dd>

</dl>

sv_prior: Compute the logarithm of the prior density for the stochastic volatility models without leverage

Description

Usage

Value

Arguments

Author

Examples