sim_marg_var: Compute a Monte Carlo estimate of the marginal variances of a...

In mcmcsae: Markov Chain Monte Carlo Small Area Estimation

Compute a Monte Carlo estimate of the marginal variances of a (I)GMRF

Description

Estimate marginal variances of a (I)GMRF prior defined in terms of a sparse precision matrix and possibly a set of equality constraints. The marginal variances might be used to rescale the precision matrix such that a default prior for a corresponding variance component is more appropriate.

Usage

sim_marg_var(
  D,
  Q = NULL,
  R = NULL,
  r = NULL,
  eps1 = 1e-09,
  eps2 = 1e-09,
  nSim = 100L
)

Arguments

D	factor of precision matrix Q such that Q=D'D.
Q	precision matrix.
R	equality restriction matrix.
r	rhs vector for equality constraints R'x = r, where R' denotes the transpose of R.
eps1	passed to create_cMVN_sampler.
eps2	passed to create_cMVN_sampler.
nSim	number of Monte Carlo samples used to estimate the marginal variances.

Value

A vector of Monte Carlo estimates of the marginal variances.

References

S.H. Sorbye and H. Rue (2014). Scaling intrinsic Gaussian Markov random field priors in spatial modelling. Spatial Statistics, 8, 39-51.

mcmcsae documentation built on April 12, 2025, 2:25 a.m.