update_fast_sv: Single MCMC Update Using Fast SV

Description Usage Arguments See Also

View source: R/stochvol-cpp-doc.R

Description

Samples the mixture indicators, the latent variables, and the model independent parameters mu, phi, and sigma. The input is the logarithm of the squared de-meaned observations. An approximate SV model is estimated instead of the exact SV model by the use of auxiliary mixture sampling. Depending on the prior specification, mu might not be updated. Depending on the expert settings, the function might follow the ancillarity-sufficiency interweaving strategy (ASIS, Yu and Meng, 2011) for sampling mu, phi, and sigma. Furthermore, the user can turn off the sampling of the parameters, the latents, or the mixture indicators in the expert settings.

Usage

1
update_fast_sv(log_data2, mu, phi, sigma, h0, h, r, prior_spec, expert)

Arguments

log_data2

log(data^2), where data is the vector of de-meaned observations

mu

parameter mu. Level of the latent process h. Updated in place

phi

parameter phi, persistence of the latent process h. Updated in place

sigma

parameter sigma, volatility of the latent process h, also called volvol. Updated in place

h0

parameter h0, the initial value of the latent process h. Updated in place

h

the vector of the latent process. Updated in place

r

the vector of the mixture indicators. Updated in place

prior_spec

prior specification object. See type_definitions.h

expert

expert settings for this function. See type_definitions.h

See Also

Other stochvol_cpp: update_general_sv(), update_regressors(), update_t_error()


stochvol documentation built on July 12, 2021, 5:08 p.m.