compute_GMRF_matrices: Compute (I)GMRF incidence, precision and restriction matrices...

In mcmcsae: Markov Chain Monte Carlo Small Area Estimation

Compute (I)GMRF incidence, precision and restriction matrices corresponding to a generic model component

Description

This function computes incidence, precision and restriction matrices, or a subset thereof, for a Gaussian Markov Random Field (GMRF). A GMRF is specified by a formula passed to the factor argument, in the same way as for the factor argument of gen.

Usage

compute_GMRF_matrices(
  factor,
  data,
  D = TRUE,
  Q = TRUE,
  R = TRUE,
  cols2remove = NULL,
  remove.redundant.R.cols = TRUE,
  enclos = .GlobalEnv,
  n.parent = 1L,
  ...
)

Arguments

factor	factor formula of a generic model component, see gen.
data	data frame to be used in deriving the matrices.
D	if TRUE compute the incidence matrix.
Q	if TRUE compute the precision matrix.
R	if TRUE compute the restriction matrix.
cols2remove	if an integer vector is passed, the dimensions (columns of D, rows and columns of Q and rows of R) that are removed. This can be useful in the case of empty domains.
remove.redundant.R.cols	whether to test for and remove redundant restrictions from restriction matrix R
enclos	enclosure to look for objects not found in data.
n.parent	for internal use; in case of custom factor, the number of frames up the calling stack in which to evaluate any custom matrices
...	further arguments passed to economizeMatrix.

Value

A list containing some or all of the components D (incidence matrix), Q (precision matrix) and R (restriction matrix).

Examples

n <- 1000
dat <- data.frame(
  x = rnorm(n),
  f1 = factor(sample(1:50, n, replace=TRUE)),
  f2 = factor(sample(1:10, n, replace=TRUE))
)
mats <- compute_GMRF_matrices(~ f1 * RW1(f2), dat)
str(mats)

mcmcsae documentation built on Oct. 11, 2023, 1:06 a.m.