RSTr (version 1.1.4)

car: 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
)

Value

An RSTr model object.

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.

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
)