dsp (version 1.2.0)

sampleBTF_sparse: Sampler for first or second order random walk (RW) Gaussian dynamic linear model (DLM) with additional shrinkage to zero

Description

Compute one draw of the T x 1 state variable mu in a DLM using back-band substitution methods. This model is equivalent to the Bayesian trend filtering (BTF) model, assuming appropriate (shrinkage/sparsity) priors for the evolution errors, with an additional shrinkage-to-zero prior.

Usage

sampleBTF_sparse(
  y,
  obs_sigma_t2,
  evol_sigma_t2,
  zero_sigma_t2,
  D = 1,
  chol0 = NULL
)

Value

T x 1 vector of simulated states

Arguments

y

the T x 1 vector of time series observations

obs_sigma_t2

the T x 1 vector of observation error variances

evol_sigma_t2

the T x 1 vector of evolution error variances

zero_sigma_t2

the T x 1 vector of shrink-to-zero variances

D

the degree of differencing (one or two)

chol0

(optional) the m x m matrix of initial Cholesky factorization; if NULL, use the Matrix package for sampling, otherwise use the spam package