calibrateModel_beyesian2: Calibrate models using Bayesian methods - employing...
In W-Mohammed/calibrater: Calibration of Decision-Analytic Models

calibrateModel_beyesian2

R Documentation

Calibrate models using Bayesian methods - employing IMIS::IMIS()

Description

Calibrate models using Bayesian methods - employing IMIS::IMIS()

Usage

calibrateModel_beyesian2(
  .b_method = "SIR",
  .func,
  .args,
  .l_targets,
  .l_params,
  .samples,
  .n_resample = 1000,
  .IMIS_sample = 1000,
  .IMIS_iterations = 30,
  .transform = FALSE
)

Arguments

`.b_method`	Character defining the Bayesian method to use in the calibration process. Currently supported methods are `SIR` and `IMIS`.
`.func`	A function defining the decision analytic model to be calibrated.
`.args`	A list of arguments passed to the model function.
`.l_targets`	A list containing a vector of targets' names, a vector of targets' weights, a vector of targets' distributions, and a table for each target that contains the values (column name 'value') and standard errors (column name 'sd') of the corresponding target.
`.l_params`	A list that contains a vector of parameter names, distributions and distributions' arguments.
`.samples`	A table or vector of sampled parameter values
`.n_resample`	the desired number of draws from the posterior
`.IMIS_sample`	the incremental sample size at each IMIS iteration
`.IMIS_iterations`	the maximum number of iterations in IMIS
`.transform`	Logical for whether to back-transform parameters to their original scale.