car: Create CAR model

In RSTr: Gibbs Samplers for Discrete Bayesian Spatiotemporal Models

Create CAR model

Description

*car() generates an RSTr model object, samples, and estimates for either an MSTCAR, MCAR, RCAR, or CAR model.

Usage

car(
  name,
  data,
  adjacency,
  dir = tempdir(),
  seed = NULL,
  perc_ci = 0.95,
  iterations = 6000,
  show_plots = TRUE,
  verbose = TRUE,
  ignore_checks = FALSE,
  method = c("binomial", "poisson"),
  impute_bounds = NULL,
  inits = NULL,
  priors = NULL
)

rcar(
  name,
  data,
  adjacency,
  dir = tempdir(),
  seed = NULL,
  perc_ci = 0.95,
  A = NULL,
  m0 = NULL,
  iterations = 6000,
  show_plots = TRUE,
  verbose = TRUE,
  ignore_checks = FALSE,
  method = c("binomial", "poisson"),
  impute_bounds = NULL,
  inits = NULL,
  priors = NULL
)

mcar(
  name,
  data,
  adjacency,
  dir = tempdir(),
  seed = NULL,
  perc_ci = 0.95,
  iterations = 6000,
  show_plots = TRUE,
  verbose = TRUE,
  ignore_checks = FALSE,
  method = c("binomial", "poisson"),
  impute_bounds = NULL,
  inits = NULL,
  priors = NULL
)

mstcar(
  name,
  data,
  adjacency,
  dir = tempdir(),
  seed = NULL,
  perc_ci = 0.95,
  iterations = 6000,
  show_plots = TRUE,
  verbose = TRUE,
  ignore_checks = FALSE,
  method = c("binomial", "poisson"),
  impute_bounds = NULL,
  inits = NULL,
  priors = NULL,
  update_rho = FALSE
)

Arguments

name	Name of model and corresponding folder.
data	Dataset including mortality (Y) and population (n) information.
adjacency	Dataset including adjacency information.
dir	Directory where model will live.
seed	Set of random seeds to use for data replication.
perc_ci	The percentage of the desired estimate credible interval. Defaults to 95 percent (0.95).
iterations	The number of iterations to run the model for.
show_plots	If set to FALSE, suppresses traceplots.
verbose	If set to FALSE, suppresses model progress messages.
ignore_checks	If set to TRUE, skips model validation.
method	Run model with either Binomial data or Poisson data.
impute_bounds	If counts are suppressed for privacy reasons, impute_bounds is the lower/upper bound of suppression, typically 0 or 1 and 10, respectively.
inits	Optional list of initial conditions for each parameter.
priors	Optional list of priors for updates.
A	For RCAR models, describes maximum intensity of smoothing between regions.
m0	For RCAR models, baseline neighbor count by region.
update_rho	For MSTCAR models, controls whether rho update is performed.

Value

An RSTr model object.

Examples

data_min <- lapply(miheart, \(x) x[1:2, 1:3, 1:3])
adj_min <- list(2, 1)
# MSTCAR model
on.exit(unlink(file.path(tempdir(), "test"), recursive = TRUE), add = TRUE)
mod_mst <- mstcar(
  name = "test",
  data = data_min,
  adjacency = adj_min,
  dir = tempdir(),
  show_plots = FALSE,
  verbose = FALSE
)

RSTr documentation built on Jan. 31, 2026, 9:07 a.m.