sampleLogVolMu: Sample the AR(1) unconditional means

In drkowal/dsp: Dynamic Shrinkage Processes

Sample the AR(1) unconditional means

Description

Compute one draw of the unconditional means in an AR(1) model with Gaussian innovations and time-dependent innovation variances. In particular, we use the sampler for the log-volatility AR(1) process with the parameter-expanded Polya-Gamma sampler. The sampler also applies to a multivariate case with independent components.

Usage

sampleLogVolMu(h, h_mu, h_phi, h_sigma_eta_t, h_sigma_eta_0, h_log_scale = 0)

Arguments

h	the T x p matrix of log-volatilities
h_mu	the p x 1 vector of previous means
h_phi	the p x 1 vector of AR(1) coefficient(s)
h_sigma_eta_t	the T x p matrix of log-vol innovation standard deviations
h_sigma_eta_0	the standard deviations of initial log-vols
h_log_scale	prior mean from scale mixture of Gaussian (Polya-Gamma) prior, e.g. log(sigma_e^2) or dhs_mean0

Value

a list containing

• the sampled mean(s) dhs_mean and

• the sampled precision(s) dhs_mean_prec_j from the Polya-Gamma parameter expansion

drkowal/dsp documentation built on July 19, 2023, 11:42 a.m.