sampleAR1: Sample the AR(1) coefficient(s)

In drkowal/dsp: Dynamic Shrinkage Processes

Sample the AR(1) coefficient(s)

Description

Compute one draw of the AR(1) coefficient in a 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

sampleAR1(h_yc, h_phi, h_sigma_eta_t, prior_dhs_phi = NULL)

Arguments

h_yc	the T x p matrix of centered log-volatilities (i.e., the log-vols minus the unconditional means dhs_mean)
h_phi	the p x 1 vector of previous AR(1) coefficient(s)
h_sigma_eta_t	the T x p matrix of log-vol innovation standard deviations
prior_dhs_phi	the parameters of the prior for the log-volatilty AR(1) coefficient dhs_phi; either NULL for uniform on [-1,1] or a 2-dimensional vector of (shape1, shape2) for a Beta prior on [(dhs_phi + 1)/2]

Value

p x 1 vector of sampled AR(1) coefficient(s)

Note

For the standard AR(1) case, p = 1. However, the function applies more generally for sampling p > 1 independent AR(1) processes (jointly).

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