sampleBTF_reg: Sampler for first or second order random walk (RW) Gaussian...

In drkowal/dsp: Dynamic Shrinkage Processes

Sampler for first or second order random walk (RW) Gaussian dynamic linear model (DLM)

Description

Compute one draw of the T x p state variable beta in a DLM using back-band substitution methods. This model is equivalent to the Bayesian trend filtering (BTF) model applied to p dynamic regression coefficients corresponding to the design matrix X, assuming appropriate (shrinkage/sparsity) priors for the evolution errors.

Usage

sampleBTF_reg(y, X, obs_sigma_t2, evol_sigma_t2, XtX, D = 1, chol0 = NULL)

Arguments

y	the T x 1 vector of time series observations
X	the T x p matrix of time series predictors
obs_sigma_t2	the T x 1 vector of observation error variances
evol_sigma_t2	the T x p matrix of evolution error variances
XtX	the Tp x Tp matrix of X'X (one-time cost; see ?build_XtX)
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

Value

T x p matrix of simulated dynamic regression coefficients beta

Note

Missing entries (NAs) are not permitted in y. Imputation schemes are available.

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