sampleDSP: Sample the dynamic shrinkage process parameters

In drkowal/dsp: Dynamic Shrinkage Processes

Sample the dynamic shrinkage process parameters

Description

Compute one draw for each of the parameters in the dynamic shrinkage process for the special case in which the shrinkage parameter kappa ~ Beta(alpha, beta) with alpha = beta. The primary example is the dynamic horseshoe process with alpha = beta = 1/2.

Usage

sampleDSP(
  omega,
  evolParams,
  sigma_e = 1,
  prior_dhs_phi = c(10, 2),
  alphaPlusBeta = 1
)

Arguments

omega	T x p matrix of evolution errors
evolParams	list of parameters to be updated (see Value below)
sigma_e	the observation error standard deviation; for (optional) scaling purposes
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]
alphaPlusBeta	For the symmetric prior kappa ~ Beta(alpha, beta) with alpha=beta, specify the sum [alpha + beta]

Value

List of relevant components:

• the T x p evolution error standard deviations sigma_wt,

• the T x p log-volatility ht, the p x 1 log-vol unconditional mean(s) dhs_mean,

• the p x 1 log-vol AR(1) coefficient(s) dhs_phi,

• the T x p log-vol innovation standard deviations sigma_eta_t from the Polya-Gamma priors,

• the p x 1 initial log-vol SD sigma_eta_0,

• and the mean of log-vol means dhs_mean0 (relevant when p > 1)

Note

The priors induced by prior_dhs_phi all imply a stationary (log-) volatility process.

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