mcmsupply (version 1.1.1)

run_jags_model: Wrapper function to run the jags model for estimating the proportion of modern contraceptive methods supplied by the public & private Sectors using a Bayesian hierarchical penalized spline model for the national and subnational administration levels

Description

Wrapper function to run the jags model for estimating the proportion of modern contraceptive methods supplied by the public & private Sectors using a Bayesian hierarchical penalized spline model for the national and subnational administration levels

Usage

run_jags_model(
  jagsdata,
  jagsparams = NULL,
  n_iter = 80000,
  n_burnin = 10000,
  n_thin = 35,
  n_chain = 2,
  n_cores = NULL,
  ...
)

Value

returns the jags model object

Arguments

jagsdata

The object from the mcmsupply::get_modelinputs() function.

jagsparams

The parameters of the JAGS model you wish to review

n_iter

Default is 80000. Number of itterations to do in JAGS model.

n_burnin

Default is 10000. Number of samples to burn-in in JAGS model.

n_thin

Default is 35. Number of samples to thin by in JAGS model.

n_chain

Default is 2. Number of chains to run in your MCMC sample.

n_cores

The number of cores to use for parallel execution in subnational estimation. If not specified, the number of cores is set to the value of options("cores"), if specified, or to approximately half the number of cores detected by the parallel package.

...

Arguments from the mcmsupply::get_modelinputs() function.

Examples

# \donttest{
raw_data <- get_data(national=TRUE, local=TRUE, mycountry="Nepal")
jagsdata <- get_modelinputs(startyear=1990, endyear=2025.5, nsegments=12, raw_data)
run_jags_model(jagsdata, n_iter=5, n_burnin=1, n_thin=1)
# }